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Food Insecurity Atlas of Orissa
VAM Unit, World Food Programme, 53 Jorbagh, New Delhi 110091. Tel - 91-11-4694381 Fax - 4627109May 2000
United Nations World Food ProgrammeIndia / ROBINS
Foreword
This first edition of the Vulnerability Analysis and Mapping of food insecurity related indicators of Orissa is intended to provide guidance on the targeting of future food security development projects in Orissa. It is the result of a considerable process of consultation, review and improvement. We are grateful for the valuable comments given by those who have already read the document. We believe improvement is a continuous process and would incorporate these changes in our forthcoming initiatives. This process does not stop with this edition and the World Food Programme in New Delhi would be grateful to receive your comments and inputs (ref: VAM unit, WFP, 53 Jor Bagh, N. Delhi, fax: 91-11-462.3422).
We wish to emphasise that the collection and mapping of secondary sources of information provides only part of the story of food insecurity. We are in the process of collecting primary data from villagers and communities and key officials in the state of Orissa. We believe this combination of primary and secondary data will more wisely inform both our analysis of the situation food insecure people live and perhaps most importantly assist in identifying development programmes which will have maximum positive impact on their lives. We are looking for partners in all these activities and should your organisation be interested in partnering with WFP, please contact us.
Finally we would like to thank the following persons and organization for collaborating in the production of this document: Government of Orissa, Dr. Dipendranath Das, and Professor Amitabh Kundu, CSRD, Jawaharlal Nehru University, New Delhi.
VAM Unit,Regional Office for Bhutan, India, Nepal and Sri Lanka53 Jor baghNew DelhiMay 2000
ContentsExecutive SummaryList of tablesList of Maps
CHAPTER – I INTRODUCTION1.1 Objectives of VAM1.2 The proposed assignment1.3 Study Plan1.4 Vulnerability Index for regional analysis 1.5 Composite Index.1.6 Cartographic Methodology1.7 Thematic mapping1.8 Limitation of the Study
CHAPTER – II INTRODUCTION TO THE STATE2.1 Physiography2.2 Climate 2.3 Area, People & Culture 2.4 Population & Demography2.5 Economy
CHAPTER – III INDICATORS
3.1 Sustenance Insecurity3.1.a Population supported by cereal production
3.1.b Seasonality3.1.c Food as percentage of household expenditure3.1.d Inadequacy of safety net system3.1.e Composite Sustenance Insecurity Index
3.2 Disaster3.2.a Cattle & Crop loss due to natural disaster3.2.b Disaster proneness3.2.c Composite Disaster
3.3 Deprivation3.3.a Percentage of Population below Poverty Line
3.3.b Scheduled Caste population.3.3.c Scheduled Tribe population.3.3.d Out Migration.3.3.e Illiteracy3.3.f Agricultural labourer3.3.g Working children3.3.h Composite Deprivation index
3.4 Gender Inequality3.4.a Disparity in literacy3.4.b Disparity in IMR3.4.c Disparity in CMR3.4.d Sex ratio3.4.e Composite gender inequality index
3.5 Malnutrition & Mortality 3.5.a Infant Mortality Rate3.5.b Child Mortality Rate3.4.c Prevalence of Malnutrition under 53.5.d Population supported by AWC3.5.e Composite Malnutrition & Mortality Index
CHAPTER – IVCOMPOSITE INDEX4.1 Composite Vulnerability Index with all Broad categories4.2 Interrelationship of Indicators4.3 Rationale behind the selection of Indicators4.4 Composite index with selected indicators4.5 Safety net coverage
CHAPTER – V COPING STRATEGY
AnnexAnnex I Reference Annex II Data SourceAnnex III TablesAnnex IV Additional Indicators
List Of Maps
1. Location Map of Orissa/Index Map2. Block map of Orissa3. Agro-ecological Zones of Orissa4. Population Supported by Cereal Production5. Seasonality in Cereal Production6. Inadequacy of Safety Net System7. Composite Sustenance Insecurity Index8. Cattle and Crop loss due to disaster9. Disaster Proneness 10. Composite Disaster Index11. Households below Poverty Line.12. Distribution of Scheduled Caste Population 13. Distribution of Scheduled Tribe Population 14. Net Out Migration 15. Illiteracy Rate16. Percentage of Agricultural Labourer 17. Working Children 18. Composite Deprivation Index19. Gender Disparity in Literacy20. Gender Disparity in IMR21. Gender Disparity in CMR22. Sex Ratio23. Composite Gender Inequality Index24. Infant Mortality Rate25. Child Mortality Rate26. Prevalence of malnutrition among under 5 Years27. Population supported by Anganwadi centre28. Composite Mortality and Malnutrition Index29. Composite Vulnerability Index with Broad Categories
List of Tables
1. Basic Demographic Indicators2. Population Supported by Cereal Production3. Seasonality in Cereal Production4. Inadequacy of Safety Net System5. Sustenance Insecurity Index6. Cattle and Crop loss index7. Disaster Proneness 8. Disaster Index9. Household below Poverty Line.10. Distribution of Scheduled Caste Population 11. Block Level Data (Table 9A, 10A, 11A, 13A, 14A & 17A)12. Distribution of Scheduled Tribe Population 13. Net Out Migration 14. Illiteracy Rate15. Percentage of Agricultural Labourer 16. Working Children 17. Deprivation Index18. Gender Disparity in Literacy19. Gender Disparity in IMR20. Gender Disparity in CMR21. Sex Ratio22. Gender Inequality Index23. Infant Mortality Rate24. Child Mortality Rate25. Prevalence of malnutrition among under 5 Years26. Population supported by Anganwadi centre27. Mortality and Malnutrition Index28. Composite Vulnerability Index with all Broad Categories29. Interrelationship of the indicators30. Composite Vulnerability Index with Selected Indicators.
31. Pattern of Safety net coverage
EXECUTIVE SUMMARY
The state of Orissa inspite of being endowed with vast natural resources has remained the second
poorest state in the country (next to Bihar), the reason for its backwardness can be attributed to natural,
social and economic factors. Extensive land degradation due to erosion, salinity, damage due to natural
disaster like drought, floods and a super cyclones can be classified under the natural causes. The high
percentage of Schedule Tribe population, low level of literacy, wide spread unemployment in rural
Orissa with almost 44 percent of people living below poverty line has worsened the situation.
It is quite revealing that while all the neighbouring states of Orissa have improved their performance in
planning and have been able to reduce percentage of population living below the poverty line, in case of
Orissa the figure has increased. Poverty gets manifested thorough high mortality and low nutrition level.
This is absolutely true for a state like Orissa, which has highest infant mortality rate and second highest
child mortality rate in the major states of India. Acute under nutrition is also a common phenomenon in
Orissa.
The objective behind the WFP project on Vulnerability Analysis and Mapping is to improve the
effectiveness of its programme by reliably identifying food insecure areas and hungry population and
targeting them for food assistance. The project has two distinctive phases:
1. Vulnerability analysis and mapping of food insecurity from secondary data.
2. Preparation of vulnerability profiles through community level assessment.
The present study involves the identification of the food insecure areas and locating them spatially. The
indicators chosen for identification of vulnerability are either reasons for food insecurity or the
manifestation of the same. The indicators are conventional and during measurement all of them have
been made unidirectional so that higher value reflects higher vulnerability. The very conventional sex
ratio has been measured here as number of males per female so that high value represents vulnerability.
Along with the measurement of individual indicators the broad input variables and output variables have
been grouped together to recognise the composite vulnerability. However the safety net variables were
kept out of the composite vulnerability as they control vulnerability. The qualitative information that
was collected from various reports on Orissa has supplemented the findings from the secondary data
analysis.
In the five broad categories of vulnerability sustenance insecurity and the disaster are the one that deals
with the component of availability. Here disaster loss, population supported for cereal production and
seasonality of cereal production was taken up. It has been found that the interior districts of Orissa are
vulnerable to sustenance, and disaster. The coastal districts although are exposed to cyclones and floods
are comparatively less vulnerable to disaster and sustenance insecurity.
The third broad category deals with the accessibility component of vulnerability where below poverty
line population, scheduled caste and tribe population, illiterates and agricultural labourers etc. have been
considered. The broad composite index indicates that the tribal and interior districts are the deprived
district inspite of being endowed with rich mineral resources.
The fifth category reflects the utilisation aspect of food and nutrition and deals with malnourished
children, IMR and CMR. It has been observed that malnutrition and mortality is more prevalent in the
coastal districts and is less in the northern region.
The analysis is comprehensive and gives an overview of the situation. The variations and deviations
from the expected results cannot be justified based on the secondary data. An in depth field study is
required to understand the regional variations and the causes of such variations. But certainly this
overview invokes the interest of further probing to realise the ground reality.
CHAPTER IINTRODUCTION
Background
Families facing chronic food insecurity are caught in a hunger trap. The inadequacy and uncertainty of
their food supply make it difficult for them to take advantage of development opportunities. The special
niche of the World Food Programme is to enable poor people to access the benefits of development by
making food available to the most vulnerable and food insecure groups.
Presently, the focus of assistance of WFP is directed towards poor children and women to meet their
special nutritional and health needs and towards the Scheduled caste and tribe who depend upon
degraded natural resources for their food security.
1.1 Objectives of Vulnerability Analysis and Mapping (VAM)
The principal objective of VAM is to increase the effectiveness of WFP aid programming by improving
the understanding of the structure of food security and vulnerability to food insecurity. Such an
understanding permits WFP to (1) accurately identify food insecure areas and populations, (2) design
food aid interventions that effectively address the needs of these people, and (3) improve the assistance
of food to them.
WFP in India has set up a VAM Unit with a view to support the country office for effective monitoring
and decision making. Indicators were selected to measure the aspects of poverty and deprivation. These
indicators were aggregated and weighted into five broad sectors, viz., (i) Sustenance Insecurity (ii)
Disasters, (iii) Deprivation & Gender Inequality (iv) Malnutrition & Mortality. Vulnerability in food and
nutrition is identified as a complex manifestation of the behaviour of these indicators where a certain
section of the population are more susceptible to adopt a worse coping mechanism if these indicators
behave in a negative manner. With the above mentioned objectives, VAM effectively explores the
population of intervention where poor food and market situation, worse poverty and gender dimension,
health and nutrition situation and ill developed disaster management operates.
1.2 The Proposed Assignment
The objective of the proposed assignment is to spatially assess the current vulnerability of the
blocks/districts on the basis of 20 individual indicators as well as on the basis of the four broad
categories. The map generated through the proposed study would depict the relative level of
development among the different districts/blocks. These maps will be used by WFP for programme
formulation, decision making and monitoring
1.3 Study Plan
The study clearly involves the following tasks:
1. Data collection,
2. Data compilation,
3. Preparing the Vulnerability Index
4. Mapping the data
5. Presentation of an analysis
6. Identify and locate the vulnerable areas spatially.
In a closed system, where there is no intervention from the market or government the agricultural
production is the most important determinant of food supply. The seasonality of cereal production also
affects the supply over different season of the year. However, in the age of democracy the scenario of
food supply is influenced by the market mechanism and government intervention.
Another important component that ensures the food availability is the household income, which helps to
procure food from the market. In a welfare state however at the time of food insecurity or at period of
crisis, to keep steady food supply, the government intervenes through different ways. Nowadays the
non-governmental developmental organisations also join hands with the government in these
intervention works. Natural disaster affects food production and influences availability of food.
Therefore agricultural productivity, its seasonality, income of the households, government/non-
government intervention (safety net) and natural disaster can be considered as the direct / proximate
determinants of food and nutrition status.
There are some variables that have very complex relationship and exert their influences in a
multidimensional way, which are very difficult to explain. E.g. a literate person would have a better
understanding of agricultural practice and disaster management, which would result in less vulnerability
to disaster and better agricultural production. This would ensure easy availability of food, presuming the
absence of any market mechanism or government intervention. A literate person would also ensure a
better job and earn a better livelihood and will be capable of ensuring steady food supply from the
market. The level of literacy also determines productivity and quality of the labourers.
The core indicators were pre selected for the study and here the scope is limited to discuss all the
relationships of the variables in details. The indicators selected for the study are as follows:
Broad Categories Individual IndicatorsSustenance Insecurity 1. Population supported by cereal production.
2. Seasonality in Cereal Production.3. Inadequacy of Safety Net System.
Broad Categories Individual IndicatorsDisasters 4. Cattle loss and Crop loss index
5. Disaster PronenessDeprivation 6. Population below Poverty Line
7. Scheduled Caste Population Index 8. Scheduled Tribe Population Index
9. Net Out Migration Index10. Illiteracy Index11. Agricultural Labourer Index12. Working Children Index
Gender 13. Gender Disparity in LiteracyInequality 14. Gender Disparity in Infant Mortality Rate
15. Gender Disparity in Child Mortality Rate16. Sex Ratio
Mortality 17. Infant Mortality Rate (IMR)& Malnutrition 18. Child Mortality Rate (CMR)
19. Prevalence of Malnutrition20. Population Supported by Anganwadi Center
1.4 Vulnerability Index For Regional Analysis:
There are three steps in the methodology of developing the vulnerability index.
i. Measurement of the individual indicators selected for the study.
ii. Developing composite index separately for the five broad categories and
iii. Finally a total composite vulnerability index.
The data for computation for all the indicators has been collected from secondary sources available
primarily from Census Report 1991, District Statistical Handbook, Government of Orissa and also from
Nodal Departments.
Measurement of the individual indicators has been done in the following way:
Individual Indicators Measurements
Population supported by 100 quintals of cereal production
Total Population (1991)/ Total cereal Production(in quintals)* 100
Seasonality in Cereal Production 1- (Second crop /first crop). {depending upon the production}
Inadequacy of Safety Net System 1. Percentage EAS beneficiaries to total agricultural worker of the districts.
2. District with CARE intervention = 13. District without CARE intervention = 04. District with WFP intervention = 15. District without WFP intervention = 0
Crop loss index Crop loss (in Rs.)per hectare of net sown area of the district.Disaster Proneness Percentage of area covered under DPAP of the total area of the
district.Households below Poverty Line Percent of households below poverty line to total rural
households of the district.SC Population Index Percent of SC population to total population.
ST Population Index Percent of ST population to total population.Net Migration (Total inter district out-migration - total inter district in -
migration) / total population of the districts. Illiteracy Index Percent Illiterate to total population (above 6 years)of the
districts.Agricultural Labourer Index Percentage of Agricultural labourers to total primary workers of
the districts.Working Children Index Percent of working children to total child population in the age
group 5-14.Gender Disparity in Literacy Ratio of male female illiteracy rates. Gender disparity in IMR Number of female infant death per 1000 male infant death.Gender disparity in CMR Number of female child death per 1000 male child death.Sex Ratio Males per 1000 females in age group 0 – 16.Infant Mortality Rate (IMR) Number of infant death per 1000 live birth.Child Mortality Rate (CMR) Number of child die by age 5 per 1000 live birth. Prevalence of Malnutrition Percent of Severely malnourished + Percent of Moderately
malnourished Children of 0-3 and 3-6 age groups to total children weighed in the district.
Population Supported by Anganwadi Centre
Total rural population of the Blocks having Anganwadi / Total number of rural Anganwadi centre in the district.
** In the next edition of this report we would incorporate the following changes - 1. Projected population figures for the ref. year of the specific indicators.2. Production data would be adjusted by deducting 'Seed-Feed and Wastage' from the total figure.
1.5 Composite Index :The most important issue of the composite index is – how to combine the different indicators into a single index reflecting the order of the regional units (districts) in terms of their level/status in a particular aspect of development. This task has been done very cautiously. In all the cases, individual indicators are measured in such a way that they can easily be ordered in a descending manner according to their values reflecting higher the value greater is the vulnerability of the district.
Then all the individual indicators have been made scale free by dividing the values of the indicators with
their statistical mean. This procedure also helps to minimise the variation of the values of the indicators
over the districts. These scale free indicators have been added up to calculate different composite
indices.
1.6 Cartographic Methodology:
The indicators measured by applying above methodology have been presented thematically. For
presentation of a data series, grouping of the data in different range is essential. Rational grouping helps
to bring out regional variation in the behaviour of a particular indicator. There are several methods
available for grouping the data. Among the well-applied methods equal range method, equal count
method, grouping by using mean and standard deviations, grouping by percentile method are some. The
present task has limited its analysis by adopting equal count and equal range method. These methods are
easy to understand and follow when wide ranges of variables are taken into account for analysis.
1.7 Thematic mapping
The indicators after measurement have been presented thematically. All the maps have four ranges - Red
representing the worst scenario, and Orange, Yellow and Green showing progressively improved status.
1.8 Limitations
For the entire set of indicators district level maps have been prepared to show the regional variation
within the state. Most of the data have been collected from the secondary sources mainly from the 1991
census, which has data for only 13 districts. Present day Orissa has 30 districts. The newly formed
districts are Bhadrak from Baleshwar, Jagatsinghpur, Kendrapara and Jajpur from Cuttack, Khurdah and
Nayagarh from Puri, Angul from Dhenkanal, Baragarh, Sonepur, Jharasuguda and Deogarh from
Sambalpur, Gajapati from Ganjam, Malkangir, Nawarangpur and Rayagada from Koraput, Nawapara
from Kalahandi and Boudh and Kandhamal have replaced Phulbani. The data for all the indicators are
not available for the newly formed districts. For those indicators the data of the parent district has been
repeated for the newly formed district.
The block level data for all the pre-selected indicators are not available at the State level Head Quarters
and it is cost in effective and time consuming for one to go and collect data from block and district level.
Block level map of few indicators whose data was readily available has been done. The Block level data
reflect the rural situation only.
CHAPTER IIINTRODUCTION TO THE STATE
2.1 Physiography
Orissa extends from 170 49’N to 220 34’N latitude and from 810 29’E to 870 29’E longitude on the
eastern coast of India. West Bengal in the northeast, Bihar in the north, Orissa in the West, Andhra
Pradesh in the south and Bay of Bengal in the east bound it. (Map no.1 and 2 - Location map of
Orissa)
Physiographically, Orissa can be divided into three broad regions. These are i) Coastal plain, ii).
Middle mountainous country and the plateau and iii) The Rolling uplands. The coastal plain, the
fertile green tract, is better known as the ‘rice bowl of Orissa’ and stretch westwards from the Eastern
coast of India, and run from the river Subernarekha in the North East to the River Rushikulya in the
South east.
The mountainous portions of Orissa covers about three-fourths of the entire state and hence determine
the economic standard of the state. The high plateau is within the mountainous areas with an average
elevation of 300-600 meters.
The rolling uplands are lower in elevation and they vary between 150 and 300 metres. These uplands are
the products of river action and are flat in nature. They are rich in soil nutrients and provide good
opportunities for cultivation of paddy in wet areas.
The rivers of Orissa are non-perennial in character, as none of them are snow fed. Most of these rivers
originate from the adjoining Chotanagpur and Amarkantak Plateau and drains into the Bay of Bengal.
The rivers originating from the Eastern Ghats are small. Mahanadi, the largest river of the State
facilitates irrigation and HydroElectric Power Generation.
2.2 Climate
The entire state lies in the Tropical Zone and is subject to high temperature. Being in the belt of medium
pressure it has medium rainfall with moderate variation in the different parts of the state. Orissa, on the
eastern seaboards of India, enjoys a tropical monsoon type of climate most of the other parts of the
country.
Orissa has a mean annual temperature of 260C. The summer temperature ranges between 33 0C to 380C
and increase from the coastal plains to the inland districts. The monsoon rainfall is of direct importance
as it controls the crop conditions in Orissa. Normal rainfall for the state is 1482mm, July and August
being the rainiest months. The winter rainfall helps the growth of a second Crop in the state.
The state can be divided into Ten Agro- Climatic zones with varied characteristics . (Map no. 3 – Agro
Climatic Zones of Orissa.)
Characteristics of Agro-Climatic zones in OrissaAgro climatic zones Climate Mean annual
rainfall (in mm )Soil group
North-western Plateau Hot and moist 1648 Red and YellowNorth central Plateau Hot and moist 1535 Red loamyNorth eastern coastal Plateau Hot and moist sub
humid1568 Alluvial
East and south eastern Plateau
Hot and humid 1449 Coastal Alluvial Saline
North eastern ghat Hot and moist sub humid
1597 Laterite and Brown Forest
Eastern ghat highland Warm and humid. 1522 RedSouth eastern ghat Warm and humid. 1522 Red, mixed red and
YellowWestern undulating Warm and moist. 1527 Black, mixed red and
BlackWest central Table land. Hot and moist 1527 Red, heavy textured
coloursMid central table land Hot and dry sub
humid.1421 Red loamy, laterite
mixed red and black.
2.3 Area people and culture
According to the 1991 census, the total land area of Orissa is 155,700 sq. km. which is about 4.7% of the
total land area of the country. As of 1991 the state was divided into 13 districts. By 1993, the state was
further subdivided and now has 30 districts.
Orissa has a rich cultural heritage. Situated at the confluence of North and south, the state has
assimilated the culture of both, forming a unique identity of its own. Orissa is the land of lord Jagannath,
whose heritage is intimately connected, with the social, cultural and religious life of the people of
Orissa. Jainism, Islam and Christianity have all had a considerable impact on the people of Orissa in
different periods. The cultural identities of the states tribal people who constitute about a quarter of the
states population have contributed different hues to the cultural landscape of the state. Orissa is also
distinguished by its arts and crafts. The temple architecture of Konark and other areas attracts world-
wide attention, and tourism is growing industry in the state.
2.4 Population and Demography
According to the 1991 census the state’s population is 31.7 million accounting for about 4 percent of the
countries population. The marginal decline in the growth rate from 20.17 percent to 20.06 percent may
be attributed to the rise in literacy rate and a subsequent acceptance of the governments family planning
programs. The density of population is 203 persons per sq. km. Within the state the population density is
higher in the coastal area than the inland districts. Thus, the problem is not of high pressure of
population but its uneven distribution.
Orissa is more rural than India. As a whole 86.6 percent of its population live in rural areas as compared
with 74 percent for the whole of India.
The crude birth rate has steadily declined from 34.6 per 1000 population in 1971 to 27.8 in 1992 for the
state and is slightly lower than the all India rate. However the TFR of 3.3 children per women is lower
than the all India rate (3.6).
The infant mortality rate of Orissa is very high, highest among the states in India. It is interesting to
observe that the life expectancy is slightly higher for males than for females in the state. The case for
India is the reverse.
The Schedule Castes constitute 16 percent (17 percent for the whole country). The state has one of the
highest concentrations of tribal in the country (22 percent as compared to 8 percent for the whole
country). The scheduled areas cover nearly 45 percent of the total geographical area. The literacy rate of
scheduled caste and scheduled tribe was 36.78 percent and 22.31 percent respectively according to the
1991 census.
Sex ratio
The sex ratio in the state reflects a better situation but recorded a decline from 981 in 1981 to 971 in
1991 (All India decline from 933 in 1981 to 927 in 1991).
Literacy
On the literacy front, the achievement has been noticeable, as the literacy rate has increased from 34
percent in 1981 to 49 percent in 1991. Although this improvement in literacy is more pronounced in the
case of females than males, female literacy levels continue to be substantially lower than male literacy
levels. The literacy rates are 63 percent for males and 35 percent for females in Orissa as compared with
64 percent and 39 percent for males and females, respectively for all India.
2.5 Economy
Agriculture continues to be the mainstay of the state’s economy absorbing about 80 percent of the total
work force and contributing 50 percent of the state’s domestic product. Paddy is the principle crop of the
state, and its cultivation is the main occupation of 75 percent of the people. Other important crops are
pulses, oilseeds, jute, mustard, sugarcane and turmeric.
In the absence of adequate irrigation facilities, agriculture has to depend on monsoons as a result of
which agricultural production fluctuates widely due to its erratic behaviour. The irrigation potential has
been created through major, medium, minor lift irrigation and water harvesting projects up to 24.04 lakh
hectares by 1997-98. The government has adopted some strategies for modernisation of present
irrigation system.
Orissa has declining forest area coverage of only 17.56 percent of the state as against the optimum
requirement of 33 percent. This drastic reduction of forests is primarily due to unauthorised felling,
forest fires, fast growing cattle population, unauthorised overgrazing, and encroachment on forestland
for cultivation, shifting cultivation and above all population explosion. This has resulted in a reduction
in rainfall, heavy increase in the frequency of floods and droughts. The increasing salinity in the soil
near the coastal areas are also contributing to the environmental degradation of the state.
The state is endowed with vast mineral deposits like coal, iron ore, manganese, dolomite, chromite, etc.
Other important minerals are limestone, bauxite, graphite, china clay, nickel, fine clay, nickel quartz
and mineral salts.
With vast mineral resources and abundance of raw materials, the state has immense potentiality for
industrialisation. Large industries like Rourkela Steel plant, national Aluminum Company (NALCO),
Indian Charge Chrome Ltd., Paradeep Phosphate, and coal based power plants at Talcher, Kaniha and
Banharpali has been set up during different plan period.
At present the Industrial Promotion and Investment Corporation limited (NPICOL), Industrial
Development Corporation Limited (IDCOL) and Orissa State Electronics Development Corporation
(OSEDC) are three nodal agencies promoting large and medium industries in the state. By the end of
1997-98 it had 313 large and medium industries. The state is providing institutional and financial
support with various incentives and concessions for promotion of small scale, and village and cottage
industries.
The physical, social, economical and demographic background of the state dictates the developmental
status of the same.
CHAPTER IIINDICATORS
3.1 SUSTENANCE INSECURITY
3.1.a Population Supported by Cereal Production:
Taking into account the high contribution of agriculture to the states income, the state government has
formulated the agricultural policy with the main objectives of doubling the production of food grains, to
generate employment opportunities and to make agriculture the main root to eradication of poverty.
However due to increase in population, the states per capita food grain production has declined. The
graph below shows the general trend of cereal production in the state over years.
In 1996-97 due to severe drought in the state there was a sharp fall in its production. Otherwise, the
production is stable.
The variable has been measured as number of people supported by 100 quintal of cereals produced in
the district assuming that the total cereal production is distributed equally amongst the population. Here
the market mechanism and governmental intervention are not considered. In an open economy with a
significant role of trading and with the presence of welfare interventions like Public Distribution System
and ICDS the pressure of population on each unit of crop produced gets reduced. All this has not been
captured in this measurement. According to the norm 100 quintal of cereals should support 49 persons
for a year (In ideal situation 206 kg of cereal should support one person for one year). The variable
indicates the population pressure on each unit of crop.
The data of cereal production used here is of 5-year average (1993-98). Thus, the effect of yearly
variation of production is minimized.
In the state, 4 districts, namely, Rayagada, Khandamal, Khurda and Jajpur have more number of persons
than this prescribed norm. Agricultural production of these districts is lower in comparison to the their
population size. The situation is satisfactory in the districts of Sambalpur, and its adjoining districts
Deogarh, Baragarh and Sonepur, Nawarangapur and Cuttack. The better irrigation facilities in
Sambalpur and adjoining districts due to presence of Hirakund Dam on Mahanadi River is likely to be
the reason for good agricultural production. Cuttack, which is situated along the lower track and upper
delta region of Mahanadi River, is also good in rice production. Lower density of population may be the
reason for low population pressure per 100 quintals of cereal in Nawarangapur.
The south and southwestern districts have shown better situation in terms of cereal availability. But, it is
to be mentioned that the south and southwestern districts dominated by tribal population have less
control over the production due more inequitable distribution of land. The distribution of land is in
favour of some higher caste population. Moreover, there is inter-border sale of food grains particularly
form Orissa to Orissa and Andhra Pradesh. (Annex: Table - 1, Map no. 4 )
3.1.b Seasonality in Cereal Production :
Agriculture in Orissa has lagged behind several developed states. The major factors contributing to low
productivity are continuance of traditional agricultural practices, inadequate capital formation,
inadequate irrigation facilities, and uneconomic size of holdings. About 70% of the total cropped area
are rainfed and exposed to the vagaries of monsoon. Technological inputs, systems of land holdings
posses equal importance as the factors like agro-climatic conditions have for the development of
agriculture.
The uncertainty of monsoons, their mal-distribution, and great variation in the amount of annual
precipitation have forced the government and the people to make provisions for artificial irrigation to
prevent frequent crop failures. Even during a good rainy season, which itself is short, the rainfall is so
erratic that the standing crop do not get water at the time when they require it most. The harvest, thus
fall far short of expectations, to the great disappointment of the rural community.
Indian agriculture is the ‘gamble of monsoon’ and this true in the scenario of agriculture of Orissa also.
That is why influence of seasonality in agriculture is very high. Most of the districts of Orissa are
overwhelmingly dependent on the production of Kharif crops to support their population. Contribution
of Rabi crops to total cereal production very less in all the districts, except Puri, Baragarh and Sonepur
yielding rather lower seasonality in these districts. (Annex: Table -2 , Map no. 5 )
Studies have shown that food availability in the rural households is closely tied to the agricultural
calendar. For the months of Oct. – Feb the food is available in the households. During the harvesting
season food availability goes up as the marginal farmers harvest their own crops. The lands less
labourers also earn some wages during this season and ensure the supply of food in the households.
Among the poor households the food supply during March – May is made from money earned through
daily wage labour (mainly in government funded construction activity). During the summer, stock of
rice gets exhausted in the household and rice becomes expensive in the market. People consume ‘saag’-
green leafy vegetables, as the rice intake goes down. The situation improves a bit in the rainy season as a
short duration paddy is harvested from their own field. In the rainy season poor households mostly
depend on forest to collect various kinds of leaves and tubers and wild fruits that are available. During
these months, government works such as roads and bridge construction also comes to temporary halt and
this result in the loss of daily wage employment. The real stressful period is Bhado- Aswin as work
availability is low and households cannot afford to purchase food items from market.
Seasonality Timeline
Jan Feb Mar Apr May Jun July Aug Sept Oct Nov Dec
Rabi
Crops Wheat, Maize, Ragi, Summer paddy, Pulses, Till and Ground nut
Kharif
Crops Winter & Autumn paddy, Potato, Sugar cane
Hungry season
3.1.c Inadequacy of Safety Net System :
The policy of the state government is to ensure availability of essential commodities to the consumers by
ensuring price stability, ensuring availability of food grains, sugar and kerosene oil and adopting a
special programme for drought prone and tribal areas. The Revamped Public Distribution System (PDS)
was implemented in ITDP & DPAP blocks and were supplied with 10 kg rice per family per month at
the specially subsidised price of Rs.2.00 per kg and all families above poverty line got the same quantity
at Rs. 4.00 per kg. The allotment of essential commodities to Orissa for distribution through PDS during
1995 to 1998 is as follows
Allotment of Essential Commodities received from Government of India
Sl. No. Commodities Unit Receipt during1995-96 1996-97 1997-98
1. Sugar Lakh MT 1.58 1.79 1.682. Wheat Lakh MT 3.50 4.51 2.193. Rice Lakh MT 7.90 10.02 5.954. Imported Edible Oil MT 10,000 7,000 8,3005. Kerosene Oil Kilo litres 2,71,728 3,00,008 3,11,419
Source: Food, Supplies and Consumer Welfare Dept. Govt. of Orissa
The percentage of households using the PDS Orissa is 5.2 as against India 33.2. The per capita
consumption of food grains met from PDS per Orissa s only 16.4 percent and percentage of requirement
of cereals met by PDS is 16.7 percent. Data on units of Ration card and Fair Price shops were not
available. However after the disastrous cyclone the position of PDS in cyclone affected districts are as
follows:
Ration Card/Position in cyclone affected districtsSl.No. Districts No of Retail No. of Families
Outlets BPL APL Total1. Cuttack 1739 174713 329506 5042192. Jagatsinghpur 916 75217 227859 3030763. Jajpur 1120 103087 226440 3295274. Kendrapara 828 84310 233884 3181945. Khurdah 879 130246 245597 3758436. Puri 811 118063 144658 2627217. Baleshwar 1462 266384 207396 4737808. Bhadrak 1089 109102 116144 2252469. Dhenkanal 844 112642 100024 21266610. Keonjhar 405 224603 135859 36046211 Nayagarh 564 104400 98786 203186
Sl.No. Districts No of Retail No. of Families
Outlets BPL APL Total12. Mayurbhanj 1915 279306 208247 48755313. Ganjam 1644 312039 306197 61823614. Gajapati 375 74871 40567 115438
Total 2019 386910 346764 733674Grand Total 14591 2168983 2621164 4790147
Other than the normal PDS there are several governmental and non-governmental interventions in the
vulnerable districts to ensure food supply. The population in these districts are supported with food
through different operational projects like wage employment programmes, integrated child development
scheme, mid day meal, food for work etc.
The index of inadequate safety net is calculated combining the three indicators - presence of CARE,
presence of WFP and percentage of EAS beneficiaries to the total agricultural workers. There are two
major wage employment programmes namely, EAS and Jawahar Rojgar Yojana (JRY) in operation in
the state. These programmes seek to provide employment for short duration in the form of casual
manual work during the lean agricultural season and also create economic infrastructure and community
assets in the rural areas. While JRY is being implemented for taking up small works according to the felt
needs to the people, EAS is implemented as a demand driven scheme under which public works are
being taken up for generation of assured employment. JRY has the objective of providing the gainful
employment to the unemployed and underemployed persons who live below the poverty line with
special preference being given to Scheduled Caste, Scheduled Tribe and women. Since, the data of
employment generated through JRY are not available at district level, only EAS is considered in the
indexing of safety net.
The map shows that coastal district (except Kendrapara and Jagatsinghpur) and districts adjacent to them
higher inadequacy of safety net index. On the other hand, northern, southern and western border districts
(except Koraput and Jharsaguda) have better safety net coverage. (Annex: Table -3, Map no. 6 )
3.1.d Percentage of Income Spent on Food:
The variable is collected and processed by National Sample Survey Organisation (NSSO) at the state
level in their various rounds over last 25 years. However, the samples drawn are such where any district
level estimates are not possible.
The NSSO Report shows that in rural Orissa a substantial proportion of expenditure of the people goes
on food items only. In general, there is a decline in the trend of expenditure on food items but according
to the 50th round (1993-94) it remains as high as above 68 percent of the total expenditure.
National Council for Applied Economic Research has done a survey during 1994 to prepare Human
Development Index. The published report contains state level data. According to the report at the state
level Orissa spends 42.7 percent of total per capita expenditure on food grains. This figure is higher than
the all India average of 30.5 per cent. In total people of Orissa spends 68.9 percent of their total income
on food whereas the national average is 63.9 percent.
3.1.e Composite Sustenance Insecurity Index.
While composing the composite sustenance insecurity composite index the intervention variable of safety net was excluded as the data reveals only the existence but not their efficiency. The scale free value of population supported by cereal production and seasonality has been added and divided by 2.
The composite scores thus obtained shows that the most vulnerable district is Khurdah, Kandhamal,
Angul, Sundergarh, and Rayagada. The districts of Baragarh, Sonepur, Sambalpur and Puri show least
venerability in terms of sustenance. . (Annex: Table - 4, Map no. -7 )
3.2 DISASTERS
3.2.a Crop Loss Index:
Orissa has been experiencing a lot of disaster due to flood havoc and famine over decades. Flood causes
damage to standing crops and to human habitation and take heavy toll in terms of human and cattle
population. Far more terrible than the floods themselves, are the post flood effects. Millions face
shortage of food. Famine and diseases sweep over the area. The countryside in Orissa gets dislocated
and cultivable lands fall barren.
The rivers that cause floods in Orissa are the Mahanadi, the Brahmani, the Baitarini, the Salandi, the
Kopali and the Subarnarekha. The eastern coastal districts are more prone to flood and cyclone damages
than the interior districts. The government has estimated the damage caused due to the recent super
cyclone in the coastal districts of Orissa. Besides the damaged caused to the population and habitat the
loss of agricultural lands is severe in the districts of Mayurbhanj, Cuttack, Bhadrak and Jajpur out of the
twelve affected districts.
The other forms of disaster, which also add to the crop loss in Orissa, are drought and cyclones. The
districts of Kalahandi, Bolangir and Baragarh faces severe drought situation.
The data on cattle loss was not available and the data of crop loss due to disaster is of 1996-97 only. The
time series data on crop loss could not be collected. Therefore, the average crop loss of the districts due
to disaster was not possible to present. The extent of crop loss has been calculated in Rs. Per hectare of
net sown area.
Stretch of districts extending in east to west direction from the coast to the western margin has higher
crop loss. Crop loss was high in the districts of Bolangir, Baragarh, Sonepur and Boudh during the
drought of 1996-97. These districts are already under the drought prone area programme (DPAP) of the
state. The other districts, which are under the DPAP, have not been affected much in that drought. The
less crop loss in the southern and northern districts of Orissa may be explained as – these districts are
already affected by the problems of soil erosion and chronic drought resulting low agricultural
productivity over the years and thus show lower loss during the drought of 1996-97. The coastal districts
also reflect moderate loss of crops due to flood. (Annex: Table - 5, Map no. - 8)
3.2.b Disaster Proneness:
Drought prone areas are characterised by degraded environment, acute soil erosion, and insufficiency of
water and moisture stress. Disaster proneness has an adverse effect on productivity. In Orissa there are 8
districts and 47 blocks of these districts are under the drought prone area programmes (DPAP) of the
state. These districts are mainly clustered in the west central part of the state except Dhenkanal, which is
in the central Orissa. These districts are away from the coast and receive less annual rainfall leading to
chronic drought in those areas. (Annex: Table - 6 , 6a, Map no. -9)
3.2.c Composite Disaster Index
The composite score of disaster was calculated dividing the aggregate value of Disaster proneness and
cattle and crop loss by 2. The districts which are most vulnerable to disaster and disaster damage –
Kandhamal, Nawapara, Baragarh Angul. Comparatively bellow districts are Cuttack Jagatsinghpur,
Ganjam, Keonjhar & Jharsaguda, Koraput, Malkangir, Sundergarh and Nawarangpur shows best
situation. (Annex: Table -7 , Map no. -10)
3.3 DEPRIVATION
3.3a Population Below Poverty line (BPL)
Orissa is the worst state in terms of poverty. Districts of Phulbani Boudh Koraput, Kalahandi,
Dhenkanal, Bolangir, Keonjhar, Mayurbhanj and Sundergarh are the worst hit by poverty. More than
65% of rural household live blow poverty line.
There are different estimates of population below ‘poverty line’ for last three decades or more. NSSO
provides Head Count Ratio (HCR) or percentage below poverty line at the national and state level. The
HCR estimates released by Planning Commission (computed using the revised expert group
methodology) for Orissa are 66.18, 70.07, 65.29 and 55.58 for 1973-74, 1977-78, 1983-84 and 1993-94
respectively. These HCR figures for all India for the said periods are 54.88, 51.32, 44.48 and 38.86
respectively. Among the states, Orissa has the highest incidence of poverty that is 31 percent higher than
the all India average. There has been an accelerated decline of HCR for all-India and Orissa, during
1980’s and early 1990’s compared to the 1970’s.
Department of Panchyati Raj provides the data on the percentage of family below poverty line (BPL) at
district level. The definition adopted here for identifying BPL is the households with income of Rs.250
per capita per month. In general, Orissa has very high incidence of poverty.
The distribution shows that the districts, which have more than 60 percent below poverty line
households, are also dominated by Scheduled Tribe population of more than 30 percent except for
Dhenkanal, Puri and Nayagarh. In Puri and Dhenkanal there are higher proportion of Scheduled Caste
population also. (Annex: Table -8 , Map no. -11)
3.3.b Scheduled Caste Population Index:
Under the Indian Constitution Scheduled Castes mean such castes or parts or groups within castes as are
declared by the President of India to be Scheduled Castes under Article-341 of the Constitution. The
persons belonging to a Scheduled Caste in a particular State or union Territory will be enumerated as
belonging to Scheduled Castes only if such a caste is listed in the Scheduled Caste list of that particular
state/union territory.
There are 93 Scheduled Castes classified in Orissa as per the Indian constitution. Indian society is
stratified on the basis of caste. People in the lower rung of the caste system are also in the bottom of the
ladder of socio-economic development. The state average of SC population is 16.20 percent. The areas
having better agricultural activities are also having higher proportion of SC population. In Orissa, the SC
population is mainly concentrated along the Mahanadi River system and its delta. Mahanadi delta region
is popularly known as the rice bowl of Orissa.
Malkangir is the only district, which has higher concentration of both Scheduled Caste and Scheduled
Tribe. The Scheduled Castes are mostly engaged in agriculture as agricultural labourers and marginal
farmers. In rural areas they also perform different caste specific occupations like carpentry, black smith
etc. (Annex: Table -9 , Map no. - 12, 12A)
3.3.c Scheduled Tribe Population Index:
Under the Indian Constitution Scheduled Tribes mean such races or tribes or parts or groups within races
or tribes as are declared by the president of India to be Scheduled Tribes under Article 342 of the
Constitution.
Orissa is one of the few states with a heavy concentration of tribal population (7.0 million) in 1991.
There are about 62 Scheduled Tribes in the State. In other words about one in every four citizens in
Orissa is a tribal and they form a major minority. They are exerting a dragging effect on the economy of
the state.
The tribes are concentrated in areas of high relief and high slopes, which sociologically suit their
environment. Their distribution pattern shows two distinct tracts of tribal concentration, the south-west
tract and the north east tract. The former consists of districts Kandhamal, Gajapati, Rayagada, Koraput,
Malkangir, Nawarangapur, Nawapara, while the latter constitute the districts of Mayurbhanj, Keonjhar,
Sundergarh, Sambalpur. (Annex: Table –9, Map no. - 13, 13A)
The Scheduled Tribes are engaged mainly in the occupation of agriculture both as cultivators and
agricultural labourers. In some parts, still now, they perform shifting cultivation following the slash and
burn method. Apart from this, they depend on the collection from the forest (mainly non-timber forest
products). Since the fifth plan period, a Tribal sub-plan has been formulated with the objectives of
improving the socio-economic conditions of the tribal population, strengthening of infrastructure in the
tribal areas, protecting the tribals against exploitation, and promoting tribal interests through legal and
administrative support.
About 58.82% of tribals work as against the state average of 43.64% and non-tribals figure of 40.44%.
Inspite of this higher participation in the workforce their low level of economy drive them to depend
more on muscle power for their livelihood. Despite some progress in the tribal regions, the tribals
seldom enjoy the fruits of planning. The higher the percentage of tribal population, the lower is the
urbanisation and hence a low development.
3.3.d. Net Migration Index:
In the scenario of migration of the state it is seen that the short distance migrants (intra-district) have
dominance over medium (inter–district) and long distance (inter-state) migrants. Short distance migrants
constitute nearly 75 percent of the total migrants of the state and these percentages for inter districts and
inter states are nearly 15 and 10 respectively.
Net migration has been measured as :
Out migration to other districts – In migration from other districts of Orissa
Total Population of the District.
The map shows that a few central, coastal and northern districts are more out-migrating. Southern,
northern and western bordering districts show more immigration This may be primarily because these
areas have better operated safety net (employment assurance scheme, Jowahar Rojgar Yojana, CARE
intervention etc.) as they are drought prone with higher concentration of ST population. (Annex: Table -10 , Map no. - 14)
3.3.e. Illiteracy:
The level of its literacy in a region or state determines the quality of population. The higher the level of
literacy greater the efficiency of the labour force. In this regard it is very unfortunate that Orissa lags far
behind the national average.
The illiteracy rate in Orissa during 1991 was 50.9 per cent against the all India average of 47.9 per cent.
While the male illiteracy rate of 36.9 per cent in the state in 1991 was nearer to the national average of
35.9 per cent, the female illiteracy stood at 65.3 per cent in 1991 which was significantly higher than the
national average of 60.7 per cent.
The map shows that all the southern districts have higher illiteracy. Proportions of tribal population are
also high in these districts. Coastal, central and northern districts (except Mayurbhanj) have lower
illiteracy index. (Annex: Table -11, Map no. -15)
To improve the literacy rates and educational levels the government has undertaken several programmes
namely, Universalisation of Elementary Education (UEE), District Primary Education Programme
(DPEP), Non-Formal Education, Mass Education (Total Literacy Campaign and Post Literacy
Campaign) etc. The improvement of literacy of the Scheduled Caste, Scheduled Tribe and women is in
special focus in the several programmes (DPEP, Non-Formal Education).
3.3.f. Agricultural Labourer Index:
The role of the agricultural sector in the states economy is crucial, as its contribution to the state income
is the highest. It provides direct and indirect employment to around 64% of the total work force.
Cultivators and agricultural labourers together constitute 63.75% of the total workers.
The data of agricultural labourers has been collected from 1991Census. These include both the marginal
cultivators and landless labourers. The block level data has been collected, compiled and has been
calculated as percent to total primary workers of the district.
The distribution shows that the districts in the central Orissa have higher proportion of agricultural
labourers. Most of the coastal districts, on the other hand, have less proportion of agricultural labourers.
All the northern districts, except Mayurbhanj and districts in the southern tip of Orissa have low
percentage of agricultural labourers. (Annex: Table - 12, Map no. -16)
3.3.g. Working Children Index:
Child Labour is not peculiar to India alone it is a global phenomenon. Although India has the largest
child labour population in the world in terms of absolute number, the proportion of working children to
the total labour force is lower in India than many other developing countries.
The distribution of child labour in various states indicates certain correlation. States having a large
population living below the poverty line have a higher incidence of child labour. Similarly, higher
incidence of child labour is accompanied by high dropout rates in schools.
Families stricken with poverty can not afford to bear educational expenses and send their children to
school. Instead, they prefer to engage them in gainful employment at an early age to enhance family
income. It is seen in the peak agricultural season families withdraw their children from school to
compensate the shortage of labour and earn higher income to cope up the low income during lean
agricultural seasons. In many a cases the long absence of the children from school ultimately leads to
drop-out.
India follows a proactive policy in the matter of tacking the problem of child labour. Article 39 under &
(f) the Directive Principles of the State Policy affirms; (e) ‘’that the health and strength of workers, men
and women, and the tender age of children are not abused and that citizens are not forced by economic
necessity to enter avocations unsuited to their age or strength;
(f) That children are given opportunities and facilities to develop in a healthy manner and in conditions
of freedom and dignity and that childhood and youth are protected against exploitation and against
moral and material abandonment.'’
In 1987 the National Child Labour Policy was adopted to deal with a situation where children work or
are compelled to work on a regular or continuous basis to earn a living for themselves and or their
family, and where conditions of work result in their being disadvantaged and exploited.
Out of 133 child labour endemic districts in 13 states of India Orissa’s contribution is of 16 districts (2 nd
highest after Maharashtra). The Child labour endemic districts in Orissa are Koraput, Ganjam,
Kalahandi, Sambalpur, Mayurbhanj, Bolangir, Malkangir, Nawarangpur, Rayagada, Nawapara,
Gajapati, Baragarh, Deogarh, Jharsaguda, Angul and Sundergarh.
On an average 5.9 percent of the children in Orissa are in the workforce. This figure is higher than the
national figure of 5.3 percent.
The distribution shows that the incidence of child labour is very high (even above 10 percent) in the
southern districts of Orissa. This region is characterised by higher level of poverty, more concentration
of Scheduled Tribe population and lower level of literacy along with higher gender disparity. Studies
have shown that the working children in Orissa are mostly engaged in the works of agriculture, cattle
raring and non-timber forest product collection. (Annex: Table - 12, Map no. - 17)
3.3.h Composite Deprivation Index
The composite deprivation index was calculated by aggregating all the scale free values and dividing
them by the number of indicators.
From the composite score that was arrived at it has been observed that Sambalpur, Deogarh, Jharsaguda,
Baragarh, etc. are the most deprived districts. Nayagarh, Baleshwar, Khurdah, Jagatsinghpur and
Dhenkanal are comparatively better.
Ganjam, Gajapati, Mayurbhanj, Bolangir reflect a better situation. (Annex: Table -13, Map no. -18).
3.4 GENDER INEQUALITY
3.4.a Gender Disparity in Literacy:
The low value attached to female education in much of India links with some deep-rooted features of
gender relations. The three very common links are as follows:
In rural India a large majority of girls are expected to spend most of their adult life in domestic work
and child rearing. Thus female education to most of the parents appears to be somewhat pointless.
The investments that parents make in the education of their daughter primarily benefit other, once
the daughter is married away. This strongly reduces the value of education from the parental self-
interest point of view.
Again, if an educated girl can only marry a more educated boy and if dowry payments increase with
education of the groom then the parents will obviously be reluctant to send their daughter for
education.
These three and other links between female education and gender relations result in female male
disparity in education.
There is a differential level of literacy among males and females. In this respect, Orissa also has figures
lower than the national average. In India while 63% of males and 32.42 percent of females were literate
in 1991, in Orissa the percentage was only 63.1 and 31.9%.
Disparity in literacy is usually measured as number of female literate per 1000 of male literate. But here
to reflect vulnerability the disparity has been measured as :
Percent of male literate to total male population
Percent of female literate to total female population.
There is a wide variation in the gender disparity of literacy. In Orissa there are 510 female literate per
1000 male literate. The south and southwestern part, areas of higher concentration of Scheduled Tribe
population, have very high gender disparity in literacy. Districts located in the rice bowl of Orissa have
lower disparity in literacy. The poor schooling facilities in the tribal areas might have resulted in higher
gender disparity in literacy there. (Annex: Table no.-14, Map No. -19)
3.4.b Gender Disparity in IMR:
Disparity in Infant Mortality Rate is measured as number of female infant death per 1000 of male infant
death.
While the levels of infant and child mortality in Orissa are very high, the gender differential in infant
mortality is not. The NFHS data in Orissa reveals that in both the neonatal and postnatal period males
have higher risks of dying than females do. The biological factor still prevails the social prejudice only
occurs after age one.
The districts with high disparity in IMR are Angul, Dhenkanal, Baragarh, Ganjam, and Sundergarh. The
districts, which have comparatively low disparity, are Kalahandi, Keonjhar and Nawapara. (Annex: Table no.- 15 , Map No. -20)
3.4.c Gender Disparity in CMR:
Child mortality in Orissa is 45 percent higher for females than for males. This reversal of sex
differentials in mortality after the age of weaning reflects the relative nutritional and medical neglect of
girls after breast-feeding has ceased. Angul, Baleshwar, Bhadrak, Bolangir Cuttack, Jagatsinghpur,
Jajpur, Kendrapara, Sonepur have high disparity in CMR. Puri, Khurdah, Nayagarh and Kalahandi
show low disparity in CMR.
The districts showing highest vulnerability of women are Nawarangpur, Sonepur, Bolangir, Boudh and
Kandhamal.
The moderates vulnerable districts are Jajpur, Kendrapara, Jharsaguda and Sundergarh whereas
comparatively better situation in Puri, Khurdah, Mayurbhanj and Nayagarh. (Annex: Table no.- 15 , Map No. –21)
3.4.d. Sex Ratio:
Sex composition in Orissa is gradually becoming more and more male dominated with each passing
decade. In 1901, there were 1,039 females per 1000 males. This declined to 1022 females in 1951 and in
1991 the figure was only 972 females per 1,000 males.
Sex ratio is generally measured as number of female per 1000 male. The data thus computed generally
reveals better situation with higher value. But since in this particular study all the indicators needs to be
unidirectional, this indicator here has been computed as male per 1000 female, revealing higher the
value more the vulnerability.
The sex ratio of Orissa as a whole is 1014 males per 1000 females in the age group of 0-16. In the age
group of 0-16 the social factors are more dominating in determining the sex ratio and in these ages the
effect of migration is very less.
The distribution reveals that a continuous belt in the northern coastal and the adjacent districts have
higher sex ratio (in favour of males). These districts are also having higher concentration of SC
population. Southern, central and western districts are having sex ratio in favour of females. These
districts are having more ST population. Sex ratio in favour of females in tribal areas are attributed to
the facts that women enjoy an equal or even higher status among tribal societies and female child is
desirable. (Annex: Table no.- 16, Map No. –22)
It has been observed that whenever both the sexes receive comparable attention and care, females have
better survival advantages over males in terms of age specific mortality rates.
3.4.e Composite Gender Inequality Index
The districts showing highest vulnerability of women are Nawarangpur, Sonepur, Bolangir, Boudh and
Kandhamal.
The moderately vulnerable districts are Jajpur, Kendrapara, Jharsaguda and Sundergarh whereas
comparatively better situation in Puri, Khurdah, Mayurbhanj and Nayagarh. (Annex: Table no.- 17 , Map No. -23)
3.5 MORTALITY AND MALNUTRITION
3.5.a Infant Mortality Rate:
Infant mortality rate (IMR) is defined as the number of death of the infants (below one year) per 1000
live births.
The level of infant mortality rate in Orissa is the highest (120) as against (80) all India average.
Accordingly to the NFHS study (1995) Neonatal and IMR for the Scheduled Tribe (113.4) are less than
the same for Scheduled Castes and other castes (160.8 & 115.0 respectively). The IMR rate is higher in
rural areas than in urban areas, 126 per 1000 live births compared with 85 per 1000. The NFHS data also
have revealed that IMR declines sharply with the increasing education of mothers
The Census of India has estimated the infant mortality rate using the indirect method of Brass technique.
Three districts (Puri, Khurdah and Nayagarh) which have very low disparity in IMR and CMR have
very IMR. Low IMR are observed in Angul, Deogarh, Dhenkanal, Keonjhar, Mayurbhanj and
Sundergarh, Sambalpur. High IMR is seen in Gajapati, Ganjam, Khurdah and Puri. (Annex: Table no.-18 , Map No. -24)
3.5.b Child Mortality Rate :
Child mortality rate (CMR) is defined as the number of death of the children below 5 years per 1000 live
births. The Census of India has estimated this child mortality rate using the indirect method of Brass
technique. The district wise picture of child mortality is more or less similar with the IMR.
Bhadrak, Puri, Kandhamal, Boudh, Khurdah and Nayagarh have high CRM, whereas low, CMR is
observed in Mayurbhanj, Sambalpur and Baragarh. (Annex: Table no.-18 , Map No. -25)
3.5. c Prevalence of Malnutrition:
Both chronic and acute under nutrition are very common in Orissa. Accordingly to the NFHS (1992)
report slightly more than half (53%) of all children are underweight and 48% are stunted. Malnutrition is
a physical manifestation of inability to receive adequate nutrition or the inability of the body to
assimilate normally. Under nutrition is lowest in the first six months when most babies are being fully
breastfed. There is a marked increase in the prevalence of under nutrition in the first year.
In Orissa malnutrition is consistently higher in rural than in urban areas. The socio-economic status of
the family and the mothers schooling are important for children’s nutritional status. Unfortunately, the
majority of young children in Orissa has illiterate mothers and is consequently at high risk of suffering
under nutrition.
Prevalence of malnutrition is measured for children below 5 years of age as weight for age as
standardised by Gomez classification. Both the categories of moderate and server malnourished are
combined to identify the percentage of malnourished children. The Data available was for children of
the age group of 0-3 and 3-6 years.
The distribution shows percentage of severely and moderately malnourished children are high in
Gajapati, Kalahandi, Boudh Nawapara, Nawarangpur and Khurdah. Comparatively less percentage are
seen in Baragarh, Mayurbhanj, Sundergarh, Cuttack, Jharsaguda, Deogarh Dhenkanal & Sambalpur.
(Annex: Table no.-19, Map No. –26A, 26B)
3.5.d Population per Anganwadi Centre (AWC):
Anganwadi centre is the unit through which the programmes of Integrated Child Development Scheme
(ICDS) are implemented. The universalised network of ICDS provides vital services in the
disadvantaged areas. They are – immunisation, Health, check up, referral services, Treatment of minor
illness, Supplementary Feeding, Growth monitoring and promotion, nutrition and health education and
early childhood care and pre-school education.
The sanctioned norm for Anganwadi Centres (AWC) is 750 population per AWC when the block is
tribal and 1000 population per AWAC when the blocks are dominated by non-tribal population. The
pressure on AWC is lower in the districts of higher tribal population. Districts with very high population
pressure per AWC are Ganjam, Kendrapara, Nayagarh, Puri, Khurdah, Dhenkanal, Bhadrak and
Baleshwar. Kandhamal Mayurbhanj, Rayagada, Sundergarh and Gajapati have low population pressure
on each Anganwadi Centre. (Annex: Table no. - 20, Map No. - 27)
3.5.e Composite Mortality and Malnutrition Index
The individual values of Infant Mortality Rate and Child Mortality Rate have been added and divided by
2 to arrive at Mortality Index. The indicator of Population supported by Anganwadi is an intervention
variable just like the safety net taking care of vulnerability, and does not add to it. This indicator has
been kept out of the composite Index.
Unit free value of Malnutrition and Mortality were aggregated and divided by the number of indicator.
Gajapati, Kalahandi Khurdah, Puri and Nawapara are mot vulnerable to mortality and malnutrition.
Mayurbhanj, Balagarh, Sundergarh, Jharsaguda and Deogarh show comparatively better situation.
(Annex: Table no.- 21, Map No. -28)
CHAPTER IVCOMPOSITE INDEX
4.1 Composite Vulnerability Index with all Broad Categories
To arrive at an overall image of the state in regard to vulnerability all the broad categories of
Vulnerability Indices were aggregated and divided by 5.
The distribution shows that the districts of Ganjam, Gajapati, Mayaurbhanj, Bhadrak, Jagatsinghpur,
Baleshwar, Keonjhar, Puri, Cuttack, Dhenkanal, Kendrapara and Jajpur are less vulnerable.
The Tribal districts of Kandhamal, Nawapara, and Baragarh, Angul Boudh, Kalahandi are the most
vulnerable to food insecurity.
The overall situation reflects that the poor deprived and tribal districts are more vulnerable to food
insecurity whereas the coastal districts are comparatively better off. (Annex: Table no.-22, Map No. -29)
4.2 Interrelationship of Indicators
Detailed nature of relationship of the indicators with each other is presented in the table of correlation
matrix and the statistically significant relationships are discussed.
Among the indicators of Sustenance Insecurity, population supported by 100 quintals of cereal and
seasonality of cereal production are found to have no significant relationship with any other indicators
(except significant association between seasonality and inadequacy of safety net system). But the
indicator inadequacy of safety net index has significant relationship with several indicators. In an
expected way, areas with higher seasonality of crop production, illiteracy, disparity in literacy, ST
population, child labour, malnutrition of the children have better safety net cover. With all these
indicators inadequacy of safety net index shows a significant negative relationship. However, the safety
net cover is less in the districts of higher IMR and CMR - which is quite unexpected.
Among the indicators of disasters, crop loss is found to be higher in the districts of higher disparity in
IMR and population per AWC, and lower in the districts of higher BPL population, ST population,
illiteracy and child labour. While the districts under DPAP have higher disparity in literacy and child
labour and lower sex ratio.
As it is expected, families below poverty line shows significant positive association with illiteracy,
disparity in literacy, ST population, child labour and malnutrition of the children (3-6) and negative
association with AWC. The indicator, Scheduled Castes (SC) has positive relationship with disparity in
CMR and AWC while negative relationship with ST population, illiteracy and malnutrition of the
children (0-3). The negative relationship of SC with illiteracy and malnutrition is quite unexpected.
Scheduled tribes show positive association with illiteracy, disparity in literacy, child labour and
malnutrition of the children and, negative association with AWC and CMR. Sex ratio shows a positive
relationship with AWC and negative relationship with disparity in literacy and child labour. Here, the
direction of relationship of sex ratio with disparity in literacy is contrary to our expectation because male
favoured sex ratio is expected to lead higher disparity in literacy. Higher illiteracy shows higher
disparity in literacy, child labour and higher malnutrition among children. The indicator is found to have
negative association with AWC. It is usually noticed that most of the child labourers are engaged in
agricultural sector. Thus, child labour shows positive association agricultural labourers. It also shows a
positive relationship with disparity in literacy and malnutrition and a negative association with AWC.
Disparity of IMR and CMR are positively related among themselves and negatively related with IMR
and CMR. Net out migration has only significant positive relationship with AWC.
IMR and CMR, like disparity in IMR and CMR, are also positively related among themselves and they
are also positively related with AWC. CMR is negatively related with ST and disparity in CMR is
positively related with SC reveals the fact of higher gender discrimination among SCs. Malnutrition of
the children 0-3 and 3-6 years show positive relationship among themselves and negative relationship
with AWC. (Annex: Table no.-23 )
4.3 Composite Index with Selected Indicators – ‘The Rationale’
Affluence has similar manifestation whereas there are different dimensions of manifestation of poverty.
Among the 20 indicators selected for the present exercise some can be grouped as input indicators, some
as intervention indicators and some as the output indicators. The input indicators are those, which are
causing vulnerability to food insecurity, e.g. Population supported by cereal production, General
Inequality Indicators and Disaster indicators. The output indicators being those which are manifestations
of vulnerability e.g. Mortality indicators and Below poverty line population. The indicators like the
safety net and population supported by Anganwadi centres in a intervention variable. They are designed
to take care of Vulnerability.
To get a perfect picture of the vulnerable regions of the state, selection of indicators and the number of
indicator chosen are essential. The regions constructed through the indicators would change with the
changing indicators.
The main objective of this exercise being mapping of vulnerability to food insecurity, it is necessary to
choose indicators that are the manifestations of poverty and food insecurity.
Four very typical indicators were chosen keeping the objective in view. They are:
1) Below Poverty Line Population – Manifestation of Poverty
2) Mortality
3) Malnutrition, both being physical manifestation of vulnerability, and
4) Migration.’
The composite index constructed with the selected indicators show that Ganjam, Gajapati, Mayurbhanj
Bolangir, Sonepur, Dhenkanal are less vulnerable to as far as these indicators are concerned.
The coastal districts of Puri, Cuttack, Keonjhar, Kalahandi are moderately vulnerable whereas the most
vulnerable districts are Deogarh, Sambalpur, Baragarh, Jharasaguda, Boudh, Sundergarh, Kandhamal &
Koraput. (Annex: Table no.- 24)
4.4 Pattern of Safety net Coverage in the State
As discussed earlier that within the 20 chosen indicators two indicators are intervention variables and
they are not manifestations of vulnerability to food insecurity and rather take care or control
vulnerability. These two are Safety net and Population Supported by Anganwadi Centre. Mapping of
these indicators was done in such a way that the data revealed more the higher the vulnerability. The
indicators were named as Inadequacy of safety net and Population supported by AWC.
Given the present situation of food insecurity to see the pattern of safety net coverage in the state of
Orissa the safety net index was calculated. The indicators were changed to Existence of Safety net and
number of AWC per 1000 population. The scale free values were aggregated and then divided by 2 to
arrive at the composite score. The composite score will reveal better coverage with higher value.
The distribution of the score shows that the vulnerable districts like Rayagada, Malkangir, Sundergarh,
Sonepur, Kandhamal, Nawapara have better safety net coverage than the coastal districts which are less
vulnerable. (Annex: Table no.-25)
CHAPTER IVCOPING STRATEGY
Physiographically Orissa can be divided into 3 broad divisions and there are 10 distinctive agro-climatic
zones. All these agro-climatic zones have distinctive characteristics and are results of different weather
conditions. As a result the kind of natural disaster which is likely to take over in these regions would
also differ. The coastal areas are more likely to face flood and cyclones whereas the inner districts would
experience drought and consecutive famine.
The coping mechanism for different kinds of natural disaster would differ with different regions and
from community to community. Different communities would have different indigenous coping
mechanisms to mitigate the effects of drought.
Look for alternative employment options / Working for long hours/ low wage
Com
mitm
ent of D
omestic
Resources
Time
LowH
igh
Borrowing grain/money
Mortgaging productive asset
Sale of Girl Child
Sale of Livestock
Mortaging of Household assets
Sale of utensils
Migration
Skipping meals
Shift to non conventional food items
Starvation
COPING STRATEGY
From a study done in the district of Bolangir1 it has been found that when there is drought the first
damage gets reflected through crop loss. There will be immediate decrease in household income and the
landless labourers working in others field will loose their employment. Lack of employment arising
from crop loss is believed to result in migration opportunities, sub normal wages delayed payment of
wages and distress.
A poor farmer first seeks loan or looks for alternative options to generate funds to mitigate his loss in the
field. This often leads to depletion of household assets, which are sold off for raising money. Scarcity of
money leads to sale of lands, mortgage of lands, sale of utensils, cattle, goat, sheep and even sale of girl
child.
In earlier days using sturdier traditional varieties of seeds of paddy could reduce the impacts of drought,
which are no longer available to the farmers and also not available in the market. During drought the
consumption pattern of the poor people also shifts to non-conventional food items. People’s dependence
on rice as a staple food declines in the wake of droughts and shifts mainly to tubers, leaves, fibres, fruits
and several forms of minor millets. Daily food intake is also reduced from thrice to twice and even to
one skimpy meal. During prolonged droughts a handful of rice is used for several times. It is tied to one
end of cloth and dipped in boiling water. Pieces of Mahua flowers are added to the boiling water with
smell of rice. The syrup thus prepared is then consumed. The rice tied in the cloth is again reused the
next day. This cycle continues till the rice totally loses its character.
People living close to forest survive on flesh of wild reptiles and animals. Small farmer owning two to
three acres of land sometimes grow vegetable to minimise stress of drought. However rarely the
situation deteriorates to starvation as the state intervenes by supplying foodgrains through the PDS .
The ultimate stress-coping mechanism is to migrate from the village to nearby urban areas in search of
employment. Popular destinations are brick kilns in Andhra Pradesh , irrigation projects within the state
or construction. Migration to urban areas enables people to tide over the lean months and earn just
enough for their subsistence.
1 Participatory Poverty Profile Study, Bolangir District, Orissa, June-Aug, 1998, DFID- Praxis.
Annex I
REFERENCES
1. State Orissa’s Environment, 1994, Council of Professional Social Workers.2. DFID Study on Orissa3. Natural Hazards Map of India, Natmo, 1991, Department of Science and Technology,
Govt. of India.4. Vulnerability Atlas of India, 1997, Building Materials and Technology Promotion
Council, Ministry of Urban Development , Govt. of India.5. IFAD evaluation of Orissa Project6. Impact of WFP Orissa Project – An Evaluation, 1995.7. WFP Generated Funds Investment on Targeted Population of Orissa.8. ‘Public Health Services and Vulnerable Groups : a study related to the issues of access,
affordability, pattern of utilization and financing in government health services in Orissa’ Oxfam, June 1999.
9. ‘Micro health and education research, Koraput site report’ Oxfam10.‘Micro health and education research, Keonjhar site report’ Oxfam11.‘Micro health and education research, Puri site report’ Oxfam12.Sinha, B. N. Geography of Orissa, National Book Trust, 199913.Economic Survey, 1998-99, Govt. of Orissa14.Status of Women in Orissa, CENDERET, Xavier Institute of Management, Orissa, 1996.15.Breaking the shackles of HUNGER, Process Documentation on the Orissa Household
Food Security Project (1993-98), UNICEF and Govt. of Orissa.16.Dreeze, Jean and Sen Amartya, India-Economic Development and Social Opportunity
Oxford University Press, Delhi., 199617.Govt. of India, Census of India, Fertility Indicators, 1991.18.Govt. of India, Final population Totals: Brief Analysis of primary Census Abstract,
Census of India (1991, Paper-2 of 1992).19.Kundu, A, Measurement of Urban Process, A study in regionalisation, Popular,
Prakashan, Bombay, 1998.20.NCAER – Human Development profile of India Inter State and Inter Groups
Differentials.Vol. II Statistical Tables, New Delhi, 1996.21.Prabhu, K. Seeta and P.C. Sarkar, Identification of Levels of Development, Economic
and Political Weekly, Vol. XXVII (36), p.p 1927-37, 1992.22.Profile of District, Centre for Monitoring Indian Economy Bombay-400025, 1993
23.Reidar Dale, Evaluation Frameworks for Development Programmes and Projects, Sage Publications India Pvt. Ltd., New Delhi, 1998.
24.UNDP Human Development Report, Oxford University Press, New Delhi- 1, 1999.25. A. Shariff and A. Kundu, State of Human Development in India and the Deprived
Districts in the Selected States, Research supported by DFID, 1998.26. A. Shariff and A. Kundu, Poverty Deprivation and Levels of Living in Andhra Pradesh,
Orissa and West Bengal, Research supported by DFID, 1998.27. Dipendra Nath Das, Child Labour in India, Sane Publications, New Delhi, 199628.Ruchi Tripathi, The Urmul experience in promoting grain banks,1998.29.Manas Ranjan Mishra, Some critical issues in KENDU leaf collection & marketing in
Orissa.30.Cyclone oB5 Eastern Orissa, India, Internal Assessment Report, Nov. 1999.31.Geeta Menon, The Impact of Migration on the Work and Status of Tribal Women in
Orissa.32.Social and Institutional analysis and livelihood systems study of tribal communities in
some selected villages in Kandhamal and gajapati districts of Orissa.
Annex II
Sources of Data:The data of the above mentioned selected indicators have been collected from different sources. The indicator, its source and year are given below:
Individual Indicators Source of data YearPopulation supported by 100 quintals of cereal production.
Govt. of Orissa, Directorate of Economics & Statistics
1993-98(5-year average)
Seasonality in Cereal Production
Govt. of Orissa, Directorate of Economics & Statistics
1993-98(5-year average
Existence of Safety Net1.Employment Assurance Scheme(EAS)2. Presence of CARE
3. Presence of WFP
Govt. of Orissa, Department of Panchayati Raj
Govt. of Orissa, Department of Women & Child DevelopmentUnited Nations World Food Programme
1999 (September)
1999
1999
Scarcity index (crop loss) Govt. of Orissa, Department of Revenue and Excise
1996-97
State declared disaster prone areas
Govt. of Orissa, Department of Rural Development
1999
Percentage of Population below Poverty Line
Govt. of Orissa, Department of Panchayati Raj
1997
Concentration of SC/ ST Census of India 1991 1991Migration (net of out and in migration)
Migration Tables, Census of India 1991
1991
Total Literacy Census of India 1991 1991Gender Disparity in Literacy Calculated from available data
from census of India 19911991
Gender disparity in IMR Estimates of child mortality indicator by sex 1991
1991
Gender disparity in CMR Estimates of child mortality indicator by sex 1991
1991
Sex Ratio Census of India 1991 1991State Declared Backward Districts
Planning Commission
Percentage of Working Children
Census of India 1991 1991
Agricultural Labourers Census of India,1991 1991Infant Mortality Rate (IMR) Estimates of child mortality
indicator by sex 19911991
Child Mortality Rate (CMR) Estimates of child mortality indicator by sex 1991
1991
Prevalence of Malnutrition Govt. of Orissa, Department of Women and Child Development
1999 (March)
Population per Anganwadi Centre
Govt. of Orissa, Department of Women and Child Development
1999
Annex III
Orissa
Table 1- POPULATION SUPPORTED BY CEREAL PRODUCTION
DISTRICT Total cereal Production (in
Qtls.)
Total
Population (1995)
Population supported by 100 quintal
cereal
Index
Angul 1972855.8 1028073 52 1.37Baleshwar 5123873.4 1814926 35 0.93
Baragarh 8092558.4 1291377 16 0.42Bhadrak 4094784.8 1182970 29 0.76Bolangir 3800137.6 1316801 35 0.91Boudh 1160774.6 339777 29 0.77Cuttack 9079733.4 2110345 23 0.61Deogarh 919116 250577 27 0.72Dhenkanal 2526795.4 1013987 40 1.06Gajapati 956847.2 486426 51 1.34Ganjam 6715099 2892674 43 1.13Jagatsinghpur 2159109.8 1084989 50 1.32Jajpur 2788330 1482868 53 1.40Jharasuguda 1213547.4 477887 39 1.04Kalahandi 3822656.2 1209788 32 0.83Kandhmal 1097204 584386 53 1.40Kendrapara 3053949.4 1229683 40 1.06Keonjhar 3554718.4 1430289 40 1.06Khurda 2530415.6 1606785 63 1.67Koraput 2734546.4 1101831 40 1.06Malkangir 1580839.4 451347 29 0.75Mayurbhanj 6245612 2016036 32 0.85Nawarangpur 3268777 905717 28 0.73Nawapara 1401483.6 502230 36 0.93Nayagarh 2380161.8 837240 35 0.94Puri 3471247.4 1396419 40 1.06Rayagada 1416254 763787 54 1.42Sambalpur 3475751.8 865449 25 0.66Sonepur 2948723.2 510075 17 0.46Sundargarh 3347018.8 1683383 50 1.32Orissa 91401089.2 33868121 37
Source: Government of Orissa, Directorate of Economic & Statistics
Table 2SEASONALITY IN CEREAL PRODUCTION (in quintal) 1993-94 to 1997-98
DISTRICT Kharif cereals
Rabi cereals Total cereal % of rabi crop
Seasonality
Angul 1873192 99663.8 1972855.8 5.05 0.95Baleshwar 4354861.8 769011.6 5123873.4 15.01 0.82Baragarh 5793747.6 2298810.8 8092558.4 28.41 0.60Bhadrak 3708632.2 386152.6 4094784.8 9.43 0.90Bolangir 3744937 55200.6 3800137.6 1.45 0.99Boudh 1134703.8 26070.8 1160774.6 2.25 0.98Cuttack 8754433.8 325299.6 9079733.4 3.58 0.96Deogarh 858454.4 60661.6 919116 6.60 0.93Dhenkanal 2431237.4 95558 2526795.4 3.78 0.96Gajapati 875403.6 81443.6 956847.2 8.51 0.91Ganjam 6658451.4 56647.6 6715099 0.84 0.99Jagatsinghpur 2013855.6 145254.2 2159109.8 6.73 0.93Jajpur 2511022.6 277307.4 2788330 9.95 0.89Jharasuguda 1195201.2 18346.2 1213547.4 1.51 0.98Kalahandi 3749878.2 72778 3822656.2 1.90 0.98Kandhmal 1049749.8 47454.2 1097204 4.33 0.95Kendrapara 2701697.6 352251.8 3053949.4 11.53 0.87Keonjhar 3453185.8 101532.6 3554718.4 2.86 0.97Khurda 2287381 243034.6 2530415.6 9.60 0.89Koraput 2279891.6 454654.8 2734546.4 16.63 0.80Malkangir 1557390 23449.4 1580839.4 1.48 0.98Mayurbhanj 6094685 150927 6245612 2.42 0.98Nawarangpur 2933866 334911 3268777 10.25 0.89Nawapara 1361692 39791.6 1401483.6 0.71 0.97Nayagarh 2363361.2 16800.6 2380161.8 2.84 0.99Puri 2384326 1086921.4 3471247.4 31.31 0.54Rayagada 1263551 152703 1416254 10.78 0.88Sambalpur 2881492.4 594259.4 3475751.8 17.10 0.79Sonepur 2269275.2 679448 2948723.2 23.04 0.70Sundargarh 3283105.2 63913.6 3347018.8 1.91 0.98Orissa 82290829.8 9110259.4 91401089.2 9.97 0.89Source: Government of Orissa, Directorate of Economics & Statistics
Table 3INADEQUACY OF SAFETY NET SYSTEM
District Total agricultural workers
Average Labour
Employed
% of EAS beneficiaries
Presence of WFP
Presence of CARE
Total Safety net Index
Angul 236353 3122 1.32 1 0 2.34 0.43Balasore 375599 646 0.17 0 0 0.17 5.88Bargarh 376039 7499 1.99 1 1 4.02 0.25Bhadrak 824524 2776 0.34 0 0 0.34 2.94Bolangir 876963 9657 1.10 1 1 3.12 0.32Boudh 409535 2070 0.51 1 1 2.51 0.40Cuttack 1341977 3418 0.25 0 0 0.26 3.92Deogarh 75812 1179 1.56 1 0 2.59 0.39Dhenkanal 695507 3549 0.51 1 0 1.52 0.66Gajapati 173604 4159 2.40 0 1 3.44 0.29Ganjam 1606202 10741 0.67 0 0 0.68 1.47Jagatsinghpur 194644 8400 4.32 0 0 4.38 0.23Jajpur 286867 4101 1.43 0 0 1.45 0.69Jharsuguda 86212 228 0.26 1 0 1.27 0.79Kalahandi 925245 8109 0.88 1 1 2.89 0.35Kandhamal 190255 2409 1.27 1 1 3.29 0.30Kendrapara 227428 6780 2.98 0 0 3.03 0.33Keonjhar 675560 1567 0.23 1 1 2.23 0.45Khurda 208586 1861 0.89 0 0 0.90 1.11Koraput 1424709 8325 0.58 1 0 1.60 0.63Malkangiri 152044 6153 4.05 1 0 5.11 0.20Mayurbhanj 1214789 10153 0.84 1 1 2.85 0.35Nabarangpur 309807 9019 2.91 1 0 3.96 0.25Nayagarh 197115 1837 0.93 0 0 0.95 1.06Nuapada 159646 2792 1.75 1 1 3.78 0.26Puri 946597 1100 0.12 0 0 0.12 8.55Rayagada 253765 10482 4.13 1 1 6.19 0.16Sambalpur 946653 13457 1.42 1 0 2.45 0.41Sonepur 150483 5081 3.38 1 0 4.43 0.23Sundargarh 304352 5585 1.84 1 1 3.86 0.26ORISSA 15846872 156254 0.99
Source: Government of Orissa, Department of Panchayati RajGovernment of Orissa, Department of Women and Child Developmentn United Nations World Food Programme
Table 4
SUSTENANCE INSECURITY INDEX
DISTRICT Population supported by 1 qtl
Seasonality in cereal
Composite Index
Angul 1.37 1.05 1.21
Baleshwar 0.93 0.92 0.92
Baragarh 0.42 0.67 0.55
Bhadrak 0.76 1.00 0.88
Bolangir 0.91 1.10 1.00
Boudh 0.77 1.09 0.93
Cuttack 0.61 1.07 0.84
Deogarh 0.72 1.03 0.88
Dhenkanal 1.06 1.07 1.06
Gajapati 1.34 1.01 1.17
Ganjam 1.13 1.10 1.12
Jagatsinghpur 1.32 1.03 1.18
Jajpur 1.40 0.99 1.20
Jharasuguda 1.04 1.10 1.07
Kalahandi 0.83 1.09 0.96
Kandhmal 1.40 1.06 1.23
Kendrapara 1.06 0.97 1.01
Keonjhar 1.06 1.08 1.07
Khurda 1.67 1.00 1.33
Koraput 1.06 0.89 0.98
Malkangir 0.75 1.10 0.92
Mayurbhanj 0.85 1.09 0.97
Nabarangpur 0.73 0.99 0.86
Nayagarh 0.93 1.11 1.02
Nuapada 0.94 1.08 1.01
Puri 1.06 0.61 0.83
Rayagada 1.42 0.98 1.20
Sambalpur 0.66 0.88 0.77
Sonepur 0.46 0.78 0.62
Sundargarh 1.32 1.09 1.21
Source: Government of Orissa, Department of Revenue and Excise
Table 5
SCARCITY DUE TO DISASTER, 1996-97
Districtcrop loss (in Rs 10
Million)Net Sown Area
(in hect.)Croploss (Rs. Per
hect net sown area)
Angul 18.67 19046 9803Baleshwar 51.3 232099 2210Baragarh 68.4 288540 2371Bhadrak 42.18 176347 2392Bolangir 81.7 287342 2843Boudh 16.34 75924 2152Cuttack 31.92 153545 2079Deogarh 0.38 54970 69Dhenkanal 31.16 138573 2249Gajapati 1.14 61559 185Ganjam 48.64 327884 1483Jagatsinghpur 18.62 111945 1663Jajpur 42.18 147743 2855Jharasuguda 7.6 55284 1375Kalahandi 33.44 264240 1266Kandhmal 7.6 83675 908Kendrapara 52.06 145111 3588Keonjhar 20.9 219305 953Khurda 35.72 118579 3012Koraput 0 405267 0Malkangir 0 117862 0Mayurbhanj 45.22 350643 1290Nawarangpur 1.14 212126 54Nawapara 43.7 111135 3932Nayagarh 8.74 133532 655Puri 36.86 135040 2730Rayagada 5.32 120745 441Sambalpur 11.2 134379 833Sonepur 34.2 97366 3513Sundargarh 0 237693 0Orissa 796.48 5017499 1587
Source: Government of Orissa, Department of Rural Development
Table 6 (a)
STATE DECLARED DROUGHT PRONE AREAS
DISTRICTS UNDER DPAP PROGRAMMEDistrict Total geographical
area (in hect.)Area under
DPAP blocks (in hect.)
No. of DPAP Blocks
% of area under DPAP
programmeAngul 521789.26 - - 0Balasore 333517.25 - - 0Bargarh 476823.58 282790 6 59.3Bhadrak 784835.03 - - 0.0Bolangir 1393578.15 378545 8 27.2Boudh 890501.2 151997 2 17.1Cuttack 1592104.39 - - 0.0Deogarh 186353.03 - - 0.0Dhenkanal 1270205.71 72661 2 5.7Gajapati 452070.33 - - 0.0Ganjam 1708352.61 - - 0.0Jagatsinghpur 175560.22 - - 0.0Jajpur 336145.91 - - 0.0Jharsuguda 176341.39 - - 0.0Kalahandi 1427301.28 450868 10 31.6Kandhamal 462473.22 462474 12 100.0Kendrapara 228511.42 - - 0.0Keonjhar 1867400.78 - - 0.0Khurda 263010.94 - - 0.0Koraput 3233416.17 - - 0.0Malkangiri 363942.74 - - 0.0Mayurbhanj 1424197.62 - - 0.0Nabarangpur 554513.77 - - 0.0Nayagarh 249931.44 - - 0.0Nuapada 318671.68 318671 5 100.0Puri 1047192.08 - - 0.0Rayagada 808498.06 - - 0.0Sambalpur 1669232.11 - - 0.0Sonepur 191436.61 67354 2 35.2Sundargarh 730320.8 - - 0.0Orissa 25138228.78 2185360 47 8.7
Source: Government of Orissa, Department of Panchayati Raj
Table 6 (b)BLOCKS UNDER DPAP
DISTRICT NAME OF THE BLOCKS
BALANGIR BelpadaBongomundaKhaprakholMuribahalPatnagarhSaintalaTitilagarhTurekela
BARAGARH BijepurGaisilatJharbandhPadampurPaikamalSohela
BOUDH HarvangaKantamal
DHENKANAL DhenkanalOdapada
KALAHANDI BhawanipatnaDharamgarhGolmundaJunagarhKalampur
KALAHANDI KesingaLanjigarhMadanpur RampurNarlaThuamul Rampur
KANDHAMAL BaligudaChakapadDaringbodiG.UdyagiriKhajuripadeKotgarhNuagoonPhiringiaPhulbaniRoikiaTikaballiTumuribandha
NAWAPARA BodenKhariarKomnaNawaparaSinapalli
SONEPUR BirmaharajpurTarva
Source: Government of Orissa, Department of Rural Development
Table 7COMPOSITE DISASTER INDEX
DISTRICT Crop loss DPAP Area Composite Index
Angul 5.17 0.00 2.58
Baleshwar 1.17 0.00 0.58
Baragarh 1.25 4.73 2.99
Bhadrak 1.26 0.00 0.63
Bolangir 1.50 2.17 1.83
Boudh 1.13 1.36 1.25
Cuttack 1.10 0.00 0.55
Deogarh 0.04 0.00 0.02
Dhenkanal 1.19 0.46 0.82
Gajapati 0.10 0.00 0.05
Ganjam 0.78 0.00 0.39
Jagatsinghpur 0.88 0.00 0.44
Jajpur 1.50 0.00 0.75
Jharasuguda 0.72 0.00 0.36
Kalahandi 0.67 2.52 1.59
Kandhmal 0.48 7.98 4.23
Kendrapara 1.89 0.00 0.95
Keonjhar 0.50 0.00 0.25
Khurda 1.59 0.00 0.79
Koraput 0.00 0.00 0.00
Malkangir 0.00 0.00 0.00
Mayurbhanj 0.68 0.00 0.34
Nabarangpur 0.03 0.00 0.01
Nayagarh 2.07 0.00 1.04
Nuapada 0.35 7.98 4.16
Puri 1.44 0.00 0.72
Rayagada 0.23 0.00 0.12
Sambalpur 0.44 0.00 0.22
Sonepur 1.85 2.81 2.33
Sundargarh 0.00 0.00 0.00
Table 8
POPULATION BELOW POVERTY LINE
DISTRICT % of population below
poverty line
%P_BPL
Angul 58.1 0.88Balasore 73.7 1.11Bargarh 60.4 0.91Bhadrak 55.3 0.83Bolangir 59.4 0.90Boudh 80.2 1.21Cuttack 50.1 0.76Deogarh 77.9 1.17Dhenkanal 68.0 1.03Gajapati 60.8 0.92Ganjam 53.5 0.81Jagatsingpur 52.5 0.79Jajpur 60.4 0.91Jharsuguda 44.3 0.67Kalahandi 63.1 0.95Kandhamal 78.4 1.18Kendrapara 55.9 0.84Keonjhar 75.0 1.13Khurda 58.3 0.88Koraput 84.6 1.28Malkangir 81.9 1.23Mayurbhanj 77.9 1.17Nabarangpur 73.7 1.11Nayagarh 64.7 0.98Nuapada 82.4 1.24Puri 71.2 1.07Rayagada 72.0 1.09Sambalpur 61.2 0.92Sonepur 69.7 1.05Sundargar 65.2 0.98ORISSA 66.0
Source: Government of Orissa, Department of Panchayati Raj
Table 9
SCHEDULED CASTES (SC) AND SCHEDULED TRIBES (ST) INDEX
DISTRICT %_SC %_STAngul 16.82 11.68
Balasore 18.57 10.57
Bargarh 18.44 19.56
Bhadrak 21.71 1.69
Bolangir 15.39 22.06
Boudh 19.64 12.92
Cuttack 18.19 3.49
Deogarh 14.60 33.31
Dhenkanal 16.03 12.68
Gajapati 8.77 47.88
Ganjam 17.91 2.93
Jagatsingpur 21.72 0.61
Jajpur 22.87 7.40
Jharsuguda 17.15 31.88
Kalahandi 17.01 28.88
Kandhamal 18.21 51.51
Kendrapara 19.83 0.40
Keonjhar 11.49 44.52
Khurda 13.62 5.14
Koraput 13.41 50.67
Malkangir 19.96 58.36
Mayurbhanj 6.99 57.87
Nabarangpur 15.09 55.27
Nayagarh 13.78 5.96
Nuapada 13.09 35.95
Puri 18.56 0.27
Rayagada 14.28 56.04
Sambalpur 17.07 35.08
Sonepur 22.11 9.50
Sundargar 8.78 50.74
ORISSA 16.0 22.0Source: Census of India 1991
Table 10
NET OUT MIGRATION INDEX
DISTRICT Net out migration
Angul 1.00
Balasore 0.43
Bargarh -4.17
Bhadrak 0.43
Bolangir 1.84
Boudh -2.51
Cuttack -2.55
Deogarh -4.17
Dhenkanal 1.00
Gajapati 4.59
Ganjam 4.59
Jagatsingpur 0.08
Jajpur 0.08
Jharsuguda -4.17
Kalahandi 0.06
Kandhamal -2.51
Kendrapara 0.08
Keonjhar -0.30
Khurda 0.00
Koraput -2.41
Malkangir -2.41
Mayurbhanj 2.76
Nabarangpur -2.41
Nayagarh 0.00
Nuapada 0.06
Puri 0.00
Rayagada -2.41
Sambalpur -4.17
Sonepur 1.84
Sundargar -3.42
Source: Migration Tables, census of India 1991
Table11
ILLITERACY
District Male literacy Female literacy Total illiteracy Total literacyAngul 67.66 34.32 48.47 51.53Balasore 71.23 43.4 42.36 57.64Bargarh 63.78 31.21 52.35 47.65Bhadrak 74.62 46.35 39.46 60.54Bolangir 55.64 21.3 61.37 38.63Boudh 60.61 21.01 59.02 40.98Cuttack 77.3 52.47 34.56 65.44Deogarh 59.23 29.26 55.55 44.45Dhenkanal 68.8 40.33 45.09 54.91Gajapati 41.76 17.44 70.63 29.37Ganjam 63.88 29.87 53.28 46.72Jagatsinghpur 78.41 52.94 34.22 65.78Jajpur 70.5 45.29 42.00 58Jharsuguda 67.21 37.01 47.36 52.64Kalahandi 46.85 15.28 68.92 31.08Kandhamal 54.68 19.82 62.77 37.23Kendrapara 76.82 50.67 36.39 63.61Keonjhar 59.04 30.01 55.27 44.73Khurda 78.7 55.39 32.28 67.72Koraput 33.99 15.15 75.36 24.64Malkangiri 28.22 11.69 79.96 20.04Mayurbhanj 21.84 23.68 62.12 37.88Nabarangpur 28.1 9.01 81.38 18.62Nayagarh 73 40.74 42.80 57.2Nuapada 42.31 12.78 72.48 27.52Puri 76.83 49.41 36.70 63.3Rayagada 36.53 15.63 73.99 26.01Sambalpur 65.94 36.48 48.44 51.56Sonepur 61.48 23.38 57.38 42.62Sundargarh 65.41 39.6 47.03 52.97ORRISA 63.09 34.68 50.91 49.09
Source: Census of India 1991
Table 12
WORKING CHILDREN AND AGRICULTURAL LABOURER INDEX
DISTRICT % of child labour to total children(5-14)
% of agricultural labourers to total primary workers
Angul 4.61 38.82
Balasore 2.01 33.64
Bargarh 7.75 40.55
Bhadrak 2.01 28.08
Bolangir 8.52 38.17
Boudh 9.49 39.27
Cuttack 1.24 36.19
Deogarh 7.75 36.28
Dhenkanal 4.61 42.27
Gajapati 8.09 40.33
Ganjam 8.09 43.19
Jagatsingpur 1.24 30.28
Jajpur 1.24 38.93
Jharsuguda 7.75 38.43
Kalahandi 12.54 45.74
Kandhamal 9.49 40.94
Kendrapara 1.24 25.83
Keonjhar 4.89 30.75
Khurda 2.44 36.27
Koraput 12.69 38.50
Malkangir 12.69 16.16
Mayurbhanj 7.34 38.83
Nabarangpur 12.69 40.04
Nayagarh 2.44 35.29
Nuapada 12.54 34.79
Puri 2.44 33.41
Rayagada 12.69 49.27
Sambalpur 7.75 43.02
Sonepur 8.52 40.36
Sundargar 6.06 29.42
ORISSA 5.87 36.77
Source: Census of India in 19991
Table 13COMPOSITE DEPRIVATION INDEX
District %BPL % SC % ST Net Migration Illiterate Child labour
Agri.Labour
Composite Index
Angul 0.88 1.03 0.46 -1.58 0.90 0.68 1.06 0.49
Baleshwar 1.11 1.13 0.41 -0.68 0.78 0.30 0.91 0.57
Baragarh 0.91 1.13 0.77 6.61 0.97 1.15 1.10 1.81
Bhadrak 0.83 1.33 0.07 -0.68 0.73 0.30 0.76 0.48
Bolangir 0.90 0.94 0.87 -2.92 1.14 1.26 1.04 0.46
Boudh 1.21 1.20 0.51 3.99 1.09 1.40 1.07 1.50
Cuttack 0.76 1.11 0.14 4.05 0.64 0.18 0.98 1.12
Deogarh 1.17 0.89 1.31 6.61 1.03 1.15 0.99 1.88
Dhenkanal 1.03 0.98 0.50 -1.58 0.84 0.68 1.15 0.51
Gajapati 0.92 0.54 1.88 -7.29 1.31 1.20 1.10 -0.05
Ganjam 0.81 1.09 0.11 -7.29 0.99 1.20 1.17 -0.27
Jagatsinghpur 0.79 1.33 0.02 -0.12 0.63 0.18 0.82 0.52
Jajpur 0.91 1.40 0.29 -0.12 0.78 0.18 1.06 0.64
Jharasuguda 0.67 1.05 1.25 6.61 0.88 1.15 1.05 1.81
Kalahandi 0.95 1.04 1.13 -0.09 1.28 1.86 1.24 1.06
Kandhmal 1.18 1.11 2.02 3.99 1.16 1.40 1.11 1.71
Kendrapara 0.84 1.21 0.02 -0.12 0.67 0.18 0.70 0.50
Keonjhar 1.13 0.70 1.75 0.48 1.02 0.72 0.84 0.95
Khurda 0.88 0.83 0.20 0.01 0.60 0.36 0.99 0.55
Koraput 1.28 0.82 1.99 3.82 1.40 1.88 1.05 1.75
Malkangir 1.23 1.22 2.29 3.82 1.48 1.88 0.44 1.77
Mayurbhanj 1.17 0.43 2.27 -4.38 1.15 1.09 1.06 0.40
Nabarangpur 1.11 0.92 2.17 3.82 1.51 1.88 1.09 1.79
Nayagarh 0.98 0.84 0.23 0.01 0.79 0.36 0.96 0.60
Nuapada 1.24 0.80 1.41 -0.09 1.34 1.86 0.95 1.07
Puri 1.07 1.13 0.01 0.01 0.68 0.36 0.91 0.60
Rayagada 1.09 0.87 2.20 3.82 1.37 1.88 1.34 1.80
Sambalpur 0.92 1.04 1.38 6.61 0.90 1.15 1.17 1.88
Sonepur 1.05 1.35 0.37 -2.92 1.06 1.26 1.10 0.47
Sundargarh 0.98 0.54 1.99 5.43 0.87 0.90 0.80 1.64
Table 15
GENDER DISPARITY IN IMR & CMR
DISTRICT Disparity in IMR Disparity in CMR
Angul 1177 1027
Balasore 830 1062
Bargarh 953 970
Bhadrak 830 1062
Bolangir 934 1083
Boudh 912 948
Cuttack 932 1123
Deogarh 953 970
Dhenkanal 1177 1027
Gajapati 955 1007
Ganjam 955 1007
Jagatsingpur 932 1123
Jajpur 932 1123
Jharsuguda 953 970
Kalahandi 695 882
Kandhamal 912 948
Kendrapara 932 1123
Keonjhar 709 993
Khurda 807 778
Koraput 908 993
Malkangir 908 993
Mayurbhanj 926 976
Nabarangpur 908 993
Nayagarh 807 778
Nuapada 695 882
Puri 807 778
Rayagada 908 993
Sambalpur 953 970
Sonepur 934 1083
Sundargar 990 991
ORRISA 860 831
Source: Estimate of Child mortality indicator by sex 1991
Table 16
SEX RATIODISTRICT Sex ratio
(male per 1000 female in 0-16 age group)
Angul 987Balasore 1017Bargarh 1003Bhadrak 1017Bolangir 1015Boudh 1004Cuttack 1023Deogarh 1003Dhenkanal 987Gajapati 1013Ganjam 1013Jagatsingpur 1023Jajpur 1023Jharsuguda 1003Kalahandi 995Kandhamal 1004Kendrapara 1023Keonjhar 1001Khurda 1021Koraput 1013Malkangir 1013Mayurbhanj 1037Nabarangpur 1013Nayagarh 1021Nuapada 995Puri 1021Rayagada 1013Sambalpur 1003Sonepur 1015Sundargar 1020ORRISA 1014
Source: Census of India in 1991
Table 14
GENDER DISPARITY IN LITERACY
DISTRICT Disparity in literacy
Angul 1.97
Balasore 1.64
Bargarh 2.04
Bhadrak 1.61
Bolangir 2.61
Boudh 2.88
Cuttack 1.47
Deogarh 2.02
Dhenkanal 1.71
Gajapati 2.39
Ganjam 2.14
Jagatsingpur 1.48
Jajpur 1.56
Jharsuguda 1.82
Kalahandi 3.07
Kandhamal 2.76
Kendrapara 1.52
Keonjhar 1.97
Khurda 1.42
Koraput 2.24
Malkangir 2.41
Mayurbhanj 0.92
Nabarangpur 3.12
Nayagarh 1.79
Nuapada 3.31
Puri 1.55
Rayagada 2.34
Sambalpur 1.81
Sonepur 2.63
Sundargar 1.65
ORRISA 1.82
Source: Census of India 1991
Table 17
DISTRICT DIS_LIT DIS_IMR DIS_CMR Males/1000Females(0-16)
Composite Index
Angul 0.96 1.30 1.04 0.98 1.07Baleshwar 0.80 0.91 1.07 1.01 0.95Baragarh 0.99 1.05 0.98 0.99 1.00Bhadrak 0.78 0.91 1.07 1.01 0.94Bolangir 1.27 1.03 1.10 1.00 1.10Boudh 1.40 1.00 0.96 0.99 1.09Cuttack 0.71 1.03 1.14 1.01 0.97Deogarh 0.98 1.05 0.98 0.99 1.00Dhenkanal 0.83 1.30 1.04 0.98 1.03Gajapati 1.16 1.05 1.02 1.00 1.06Ganjam 1.04 1.05 1.02 1.00 1.03Jagatsinghpur 0.72 1.03 1.14 1.01 0.97Jajpur 0.75 1.03 1.14 1.01 0.98Jharasuguda 0.88 1.05 0.98 0.99 0.98Kalahandi 1.49 0.77 0.89 0.98 1.03Kandhmal 1.34 1.00 0.96 0.99 1.07Kendrapara 0.74 1.03 1.14 1.01 0.98Keonjhar 0.95 0.78 1.00 0.99 0.93Khurda 0.69 0.89 0.79 1.01 0.84Koraput 1.09 1.00 1.00 1.00 1.02Malkangir 1.17 1.00 1.00 1.00 1.04Mayurbhanj 0.45 1.02 0.99 1.03 0.87Nabarangpur 1.51 1.00 1.00 1.00 1.13Nayagarh 0.87 0.89 0.79 1.01 0.89Nuapada 1.61 0.77 0.89 0.98 1.06Puri 0.75 0.89 0.79 1.01 0.86Rayagada 1.13 1.00 1.00 1.00 1.04Sambalpur 0.88 1.05 0.98 0.99 0.98Sonepur 1.28 1.03 1.10 1.00 1.10Sundargarh 0.80 1.09 1.00 1.01 0.98
Table 18
INFANT AND CHILD MORTALITY RATE, 1991
District IMR CMR
Angul 105 148Balasore 123 164
Bargarh 103 131
Bhadrak 123 164
Bolangir 101 139
Boudh 119 170
Cuttack 112 142
Deogarh 103 131
Dhenkanal 105 148
Gajapati 133 149
Ganjam 133 149
Jagatsinghpur 112 142
Jajpur 112 142
Jharsuguda 103 131
Kalahandi 137 158
Kandhamal 119 170
Kendrapara 112 142
Keonjhar 99 137
Khurda 151 172
Koraput 118 140
Malkangiri 118 140
Mayurbhanj 91 125
Nabarangpur 118 140
Nayagarh 151 172
Nuapada 137 158
Puri 151 172
Rayagada 118 140
Sambalpur 103 131
Sonepur 101 139
Sundargarh 101 115ORISSA 125 133
Source: Estimates of Child mortality indicator by sex 1991
Table 19
PERCENTAGE OF CILDREN SUFFERING FROM MALNUTRITION, 1998
District Malnourished children (0-3 years)
Malnourished children (3-6 years)
Angul 32.29 26.27
Balasore 25.73 24.01
Bargarh 25.79 20.67
Bhadrak 23.41 23.48
Bolangir 30.63 29.02
Boudh 35.15 29.11
Cuttack 23.48 20.93
Deogarh 28.79 25.79
Dhenkanal 24.29 24.92
Gajapati 49.40 31.17
Ganjam 26.70 24.73
Jagatsinghpur 26.57 24.78
Jajpur 29.02 28.34
Jharsuguda 30.54 22.94
Kalahandi 33.62 31.18
Kandhamal 29.49 23.65
Kendrapara 26.44 23.99
Keonjhar 32.30 29.62
Khurda 26.22 21.88
Koraput 32.38 29.04
Malkangiri 30.39 26.22
Mayurbhanj 30.04 25.79
Nabarangpur 36.52 32.77
Nayagarh 25.25 17.45
Nuapada 32.04 28.52
Puri 24.00 21.61
Rayagada 33.13 30.20
Sambalpur 29.10 27.17
Sonepur 31.99 28.40
Sundargarh 31.09 24.46
ORISSA 30.50 26.62
Source: Government of Orissa, Department of Women and Child Development
Table 20POPULATION SUPPORTED BY ANGANWADI CENTRE
District Number of rural anganwadi
centre(AWC)
Total rural population Population per rural AWC
Angul 695 973551 1401Balasore 981 1765116 1799Bargarh 1193 1076969 903Bhadrak 580 1139788 1965Bolangir 1281 1206868 942Boudh 417 345788 829Cuttack 1155 1701543 1473Deogarh 294 248287 845Dhenkanal 691 995328 1440Gajapati 631 466620 739Ganjam 1264 2609517 2064Jagatsinghpur 727 1073594 1477Jajpur 795 1525159 1918Jharsuguda 433 328891 760Kalahandi 1163 1204727 1036Kandhamal 963 584339 607Kendrapara 588 1243094 2114Keonjhar 1559 1336528 857Khurda 781 1128046 1444Koraput 1289 978156 759Malkangiri 580 443432 765Mayurbhanj 2994 2023630 676Nabarangpur 994 920696 926Nayagarh 383 865607 2260Nuapada 585 507778 868Puri 491 1306744 2661Rayagada 1001 714842 714Sambalpur 786 634074 807Sonepur 416 505796 1216Sundargarh 1726 1195010 692ORISSA 27436 31049519 1132
Source : Govt. of Orissa, Department of Women and Child Development.
Table 21
COMPOSITE MORTALITY AND MALNUTRITION INDEX
DISTRICT Mortality Malnutrition Composite Index
Angul 0.95 2.48 1.71
Baleshwar 1.08 2.52 1.80
Baragarh 0.89 2.16 1.52
Bhadrak 1.08 2.47 1.78
Bolangir 0.91 2.43 1.67
Boudh 1.09 2.78 1.93
Cuttack 0.96 2.24 1.60
Deogarh 0.89 2.31 1.60
Dhenkanal 0.95 2.32 1.63
Gajapati 1.08 3.04 2.06
Ganjam 1.08 2.54 1.81
Jagatsinghpur 0.96 2.37 1.66
Jajpur 0.96 2.48 1.72
Jharasuguda 0.89 2.28 1.58
Kalahandi 1.12 2.85 1.99
Kandhmal 1.09 2.58 1.83
Kendrapara 0.96 2.35 1.66
Keonjhar 0.89 2.45 1.67
Khurda 1.23 2.71 1.97
Koraput 0.98 2.57 1.78
Malkangir 0.98 2.49 1.73
Mayurbhanj 0.81 2.22 1.52
Nabarangpur 0.98 2.71 1.85
Nayagarh 1.23 2.61 1.92
Nuapada 1.12 2.77 1.95
Puri 1.23 2.67 1.95
Rayagada 0.98 2.61 1.79
Sambalpur 0.89 2.34 1.61
Sonepur 0.91 2.44 1.67
Sundargarh 0.82 2.23 1.53
Table-22
COMPOSITE INDEX WITH ALL BROAD INDICATORS
DISTRICT Sustenance Disaster Deprivation Gender Inequality
Malnutrition &Mortality
Composite
Angul 1.21 2.58 0.49 1.07 1.71 1.41
Baleshwar 0.92 0.58 0.57 0.95 1.80 0.97
Baragarh 0.55 2.99 1.81 1.00 1.52 1.57
Bhadrak 0.88 0.63 0.48 0.94 1.78 0.94
Bolangir 1.00 1.83 0.46 1.10 1.67 1.21
Boudh 0.93 1.25 1.50 1.09 1.93 1.34
Cuttack 0.84 0.55 1.12 0.97 1.60 1.02
Deogarh 0.88 0.02 1.88 1.00 1.60 1.07
Dhenkanal 1.06 0.82 0.51 1.03 1.63 1.01
Gajapati 1.17 0.05 -0.05 1.06 2.06 0.86
Ganjam 1.12 0.39 -0.27 1.03 1.81 0.81
Jagatsinghpur 1.18 0.44 0.52 0.97 1.66 0.96
Jajpur 1.20 0.75 0.64 0.98 1.72 1.06
Jharasuguda 1.07 0.36 1.81 0.98 1.58 1.16
Kalahandi 0.96 1.59 1.06 1.03 1.99 1.33
Kandhmal 1.23 4.23 1.71 1.07 1.83 2.02
Kendrapara 1.01 0.95 0.50 0.98 1.66 1.02
Keonjhar 1.07 0.25 0.95 0.93 1.67 0.97
Khurda 1.33 0.79 0.55 0.84 1.97 1.10
Koraput 0.98 0.00 1.75 1.02 1.78 1.10
Malkangir 0.92 0.00 1.77 1.04 1.73 1.09
Mayurbhanj 0.97 0.34 0.40 0.87 1.52 0.82
Nabarangpur 0.86 0.01 1.79 1.13 1.85 1.13
Nayagarh 1.02 1.04 0.60 0.89 1.92 1.09
Nuapada 1.01 4.16 1.07 1.06 1.95 1.85
Puri 0.83 0.72 0.60 0.86 1.95 0.99
Rayagada 1.20 0.12 1.80 1.04 1.79 1.19
Sambalpur 0.77 0.22 1.88 0.98 1.61 1.09
Sonepur 0.62 2.33 0.47 1.10 1.67 1.24
Sundargarh 1.21 0 1.64 0.98 1.53 1.07
Table: 23
Correlation Coefficients
VAR00001 VAR00002 VAR00003 VAR00004 VAR00005 VAR00006VAR00001 1.0000 .2591 -.0572 .1317 -.1269 -.2045VAR00002 .2591 1.0000 -.4750** -.0882 -.0606 .1198VAR00003 -.0572 -.4750** 1.0000 .1314 -.2070 -.3470*VAR00004 .1317 -.0882 .1314 1.0000 -.0826 -.2303VAR00005 -.1269 -.0606 -.2070 -.0826 1.0000 .5811**VAR00006 -.2045 .1198 -.3470* -.2303 .5811** 1.0000VAR00007 .1025 .0454 -.2313 .3458* -.2480 -.2435VAR00008 -.1148 .1237 -.1739 .0647 -.1796 -.1470VAR00009 .0713 -.1167 .2870 -.1494 -.3673* -.5147**VAR00010 -.1427 -.0581 -.0669 -.3668* .2949 .4079*VAR00011 -.2256 -.2889 .2333 .3026 .0713 .0339VAR00012 .0284 .2190 -.4441** -.6059** .1468 .3551*VAR00013 .2473 .1405 .1032 .2944 -.0915 -.0749VAR00014 -.1666 .1661 -.4512** -.4653** .2994 .7470**VAR00015 -.2163 .1127 -.4698** -.4779** .3823* .7813**VAR00016 .0523 -.0841 -.1725 .0231 .1857 .2691VAR00017 .0975 -.2724 .6457** .4762** -.3045 -.4328**VAR00018 .2797 -.1000 .4178* .0126 .0719 .1701VAR00019 .2085 -.0526 .4436** .2677 .2290 .1806VAR00020 .1491 .1869 -.4421** -.2512 .0519 .5431**VAR00021 .0156 .1678 -.4196* -.2987 .0352 .6063**
* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed
VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages
Correlation Coefficients - -(CONTD…)
VAR00007 VAR00008 VAR00009 VAR00010 VAR00011 VAR00012VAR00001 .1025 -.1148 .0713 -.1427 -.2256 .0284VAR00002 .0454 .1237 -.1167 -.0581 -.2889 .2190VAR00003 -.2313 -.1739 .2870 -.0669 .2333 -.4441**VAR00004 .3458* .0647 -.1494 -.3668* .3026 -.6059**VAR00005 -.2480 -.1796 -.3673* .2949 .0713 .1468VAR00006 -.2435 -.1470 -.5147** .4079* .0339 .3551*VAR00007 1.0000 .4435** -.1873 -.2447 .0678 -.0527VAR00008 .4435** 1.0000 .1329 -.2801 .3578* -.1068VAR00009 -.1873 .1329 1.0000 -.1214 -.0396 -.1065VAR00010 -.2447 -.2801 -.1214 1.0000 -.2745 .5570**VAR00011 .0678 .3578* -.0396 -.2745 1.0000 -.6053**VAR00012 -.0527 -.1068 -.1065 .5570** -.6053** 1.0000VAR00013 -.0041 .1131 .1961 -.1514 -.1116 -.2882VAR00014 -.1251 -.0856 -.2622 .6178** -.3324* .7937**VAR00015 -.1069 -.1929 -.3759* .5330** -.2637 .7299**VAR00016 .1656 -.1244 -.3042 -.0647 -.1529 .0772VAR00017 -.0835 -.0450 .3120* -.3743* .4515** -.8132**VAR00018 -.5180** -.6550** .0930 .0210 .0320 -.2799VAR00019 -.3902* -.4783** -.0711 .1013 .2761 -.4378**VAR00020 .0034 .0078 -.1876 .2381 -.4353** .5781**VAR00021 -.0692 .2379 -.2614 .3636* -.1733 .5077**
* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed
VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages
Correlation Coefficients - -(CONTD…)
VAR00013 VAR00014 VAR00015 VAR00016 VAR00017 VAR00018
VAR00001 .2473 -.1666 -.2163 .0523 .0975 .2797VAR00002 .1405 .1661 .1127 -.0841 -.2724 -.1000VAR00003 .1032 -.4512** -.4698** -.1725 .6457** .4178*VAR00004 .2944 -.4653** -.4779** .0231 .4762** .0126VAR00005 -.0915 .2994 .3823* .1857 -.3045 .0719VAR00006 -.0749 .7470** .7813** .2691 -.4328** .1701VAR00007 -.0041 -.1251 -.1069 .1656 -.0835 -.5180**VAR00008 .1131 -.0856 -.1929 -.1244 -.0450 -.6550**VAR00009 .1961 -.2622 -.3759* -.3042 .3120* .0930VAR00010 -.1514 .6178** .5330** -.0647 -.3743* .0210VAR00011 -.1116 -.3324* -.2637 -.1529 .4515** .0320VAR00012 -.2882 .7937** .7299** .0772 -.8132** -.2799VAR00013 1.0000 -.0504 -.2073 .0764 .3845* .2479VAR00014 -.0504 1.0000 .9333** .2082 -.6667** -.0617VAR00015 -.2073 .9333** 1.0000 .3175* -.7097** -.0568VAR00016 .0764 .2082 .3175* 1.0000 -.2107 -.0058VAR00017 .3845* -.6667** -.7097** -.2107 1.0000 .4858**VAR00018 .2479 -.0617 -.0568 -.0058 .4858** 1.0000VAR00019 .2621 -.1828 -.1952 .0192 .4889** .7972**VAR00020 .1740 .6733** .5604** .2549 -.5760** -.0303VAR00021 .1406 .7089** .6218** .2937 -.5117** -.2061
* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed
VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages
Correlation Coefficients - -(CONTD…)
VAR00019 VAR00020 VAR00021
VAR00001 .2085 .1491 .0156VAR00002 -.0526 .1869 .1678VAR00003 .4436** -.4421** -.4196*VAR00004 .2677 -.2512 -.2987VAR00005 .2290 .0519 .0352VAR00006 .1806 .5431** .6063**VAR00007 -.3902* .0034 -.0692VAR00008 -.4783** .0078 .2379VAR00009 -.0711 -.1876 -.2614VAR00010 .1013 .2381 .3636*VAR00011 .2761 -.4353** -.1733VAR00012 -.4378** .5781** .5077**VAR00013 .2621 .1740 .1406VAR00014 -.1828 .6733** .7089**VAR00015 -.1952 .5604** .6218**VAR00016 .0192 .2549 .2937VAR00017 .4889** -.5760** -.5117**VAR00018 .7972** -.0303 -.2061VAR00019 1.0000 -.1552 -.2318VAR00020 -.1552 1.0000 .7471**VAR00021 -.2318 .7471** 1.0000
* - Signif. LE .05 ** - Signif. LE .01 (1-tailed)" . " is printed if a coefficient cannot be computed
VAR001 Population supported by cereal production.VAR002 Seasonality in Cereal ProductionVAR003 Inadequacy of Safety Net systemInVAR004 Crop Loss IndexVAR005 Disaster PronenessVAR006 Gender Disparity in LiteracyVAR007 Gender disparity in IMRVAR008 Gender disparity in CMRVAR009 Sex RatioVAR0010 Population below Poverty LineVAR0011 SC Population IndexVAR0012 ST Population IndexVAR0013 Net Out Migration IndexVAR0014 Illiteracy IndexVAR0015 Agricultural labourer IndexVAR0016 Working Children IndexVAR0017 Population per Anganwadi Centre(AWC)VAR0018 Infant Mortality Rate (IMR)VAR0019 Child Mortality Rate (CMR)VAR0020 Prevalence Malnutrition 0-3 agesVAR0021 Prevalence Malnutrition 3-6 ages
Table: 24
COMPOSITE INDEX WITH SELECTED INDICATORS
DISTRICT %P BPL Mortality Malnutrition Net Migration
Composite
Angul 0.88 0.95 2.48 -1.58 0.68Baleshwar 1.11 1.08 2.52 -0.68 1.01Baragarh 0.91 0.89 2.16 6.61 2.64Bhadrak 0.83 1.08 2.47 -0.68 0.93Bolangir 0.90 0.91 2.43 -2.92 0.33Boudh 1.21 1.09 2.78 3.99 2.27Cuttack 0.76 0.96 2.24 4.05 2.00Deogarh 1.17 0.89 2.31 6.61 2.75Dhenkanal 1.03 0.95 2.32 -1.58 0.68Gajapati 0.92 1.08 3.04 -7.29 -0.56Ganjam 0.81 1.08 2.54 -7.29 -0.72Jagatsinghpur 0.79 0.96 2.37 -0.12 1.00Jajpur 0.91 0.96 2.48 -0.12 1.06Jharasuguda 0.67 0.89 2.28 6.61 2.61Kalahandi 0.95 1.12 2.85 -0.09 1.21Kandhmal 1.18 1.09 2.58 3.99 2.21Kendrapara 0.84 0.96 2.35 -0.12 1.01Keonjhar 1.13 0.89 2.45 0.48 1.24Khurda 0.88 1.23 2.71 0.01 1.21Koraput 1.28 0.98 2.57 3.82 2.16Malkangir 1.23 0.98 2.49 3.82 2.13Mayurbhanj 1.17 0.81 2.22 -4.38 -0.04Nabarangpur 1.11 0.98 2.71 3.82 2.16Nayagarh 0.98 1.23 2.61 0.01 1.20Nuapada 1.24 1.12 2.77 -0.09 1.26Puri 1.07 1.23 2.67 0.01 1.24Rayagada 1.09 0.98 2.61 3.82 2.12Sambalpur 0.92 0.89 2.34 6.61 2.69Sonepur 1.05 0.91 2.44 -2.92 0.37Sundargarh 0.98 0.82 2.23 5.43 2.37
Table 25
PATTERN OF SAFETY NET COVERAGE
District Number of rural
Anganwadi centre(AWC)
Total rural population
AWC/1000 pop
AWC index
Safety netindex
Compositeindex
Angul 695 850729 0.82 0.74 2.34 1.54Balasore 981 1542431 0.64 0.57 0.17 0.37Bargarh 1193 941100 1.27 1.14 4.02 2.58Bhadrak 580 995993 0.58 0.52 0.34 0.43Bolangir 1281 1054611 1.21 1.09 3.12 2.11Boudh 417 302164 1.38 1.24 2.51 1.88Cuttack 1155 1486878 0.78 0.70 0.26 0.48Deogarh 294 216963 1.36 1.22 2.59 1.90Dhenkanal 691 869758 0.79 0.72 1.52 1.12Gajapati 631 407752 1.55 1.39 3.44 2.42Ganjam 1264 2280303 0.55 0.50 0.68 0.59Jagatsinghpur 727 938150 0.77 0.70 4.38 2.54Jajpur 795 1332746 0.60 0.54 1.45 0.99Jharsuguda 433 287398 1.51 1.36 1.27 1.31Kalahandi 1163 1052740 1.10 1.00 2.89 1.94Kandhamal 963 510619 1.89 1.70 3.29 2.49Kendrapara 588 1086266 0.54 0.49 3.03 1.76Keonjhar 1559 1167913 1.33 1.20 2.23 1.72Khurda 781 985733 0.79 0.71 0.90 0.81Koraput 1289 854753 1.51 1.36 1.60 1.48Malkangiri 580 387489 1.50 1.35 5.11 3.23Mayurbhanj 2994 1768331 1.69 1.53 2.85 2.19Nabarangpur 994 804542 1.24 1.11 3.96 2.54Nayagarh 383 756403 0.51 0.46 0.95 0.70Nuapada 585 443717 1.32 1.19 3.78 2.48Puri 491 1141886 0.43 0.39 0.12 0.25Rayagada 1001 624658 1.60 1.44 6.19 3.82Sambalpur 786 554080 1.42 1.28 2.45 1.86Sonepur 416 441985 0.94 0.85 4.43 2.64Sundargarh 1726 1044249 1.65 1.49 3.86 2.68
Annex IV
ADDITIONAL INDICATORS RELATED TO FOOD SECURITY [Availability with the sources]
Sl.No
Indicator Sources with contact person Level latest period of availability
Comments
1 Number of beneficiaries receiving food aid including mid-day meal
Deputy Secretary, Nutrition, Department of Women and Child Development (ICDS- IV)
Project/Block
1998 Family income Rs. <=20,000 per year
2. Prevalence of protein/energy malnutrition
Not Available
3. Population Growth Rate
Census of India, 1991, District Census Hand Book, Orissa
Village 1991
4. Population Density per sq. km.
Census of India, 1991, District Census Hand Book, Orissa
Village 1991
5. Percentage planted to cash crop of cultivated area
District Statistical Handbook, Directorate of Economics and Statistics, Govt. of Orissa
District 1995
6. School Enrolment by SC/ST
Orissa Primary Education Programme Authority(OPEPA) Got. Of Orissa
Block 1998
7. School Enrolment by Gender
Do Block 1998
8. Mean price of wheat over 10 years
Price Section, Directorate of Economics and Statistics, Govt. of Orissa
District 1998
9. Mean price of rice over 10 years
Price Section, Directorate of Economics and Statistics
District 1998 PDS/ Fair price shops beneficiaries
10 Mean price of pulses over 10 years
Price Section, Directorate of Economics and Statistics
District 1998
11 Irrigated land as District Statistical Handbook, Directorate of Block 1995
percentage to total cultivable land
Economics and Statistics, Govt. of Orissa
12 Crop yield per unit area by years
Directorate of Economics and Statistics, Govt. of Orissa
District 1997-98
13 Crop yield per unit area by crops
Directorate of Economics and Statistics, Govt. of Orissa
District 1997-98
14 Average size of households
Census of India, 1991, District Census Hand Book, Orissa
Village 1991
15 Percentage of villages with safe drinking water facility
Census of India, 1991, District Census Hand Book, Orissa
Block 1991
16 Percentage of villages with PDS shop within 10 km
Not available
17 Percentage of villages with market within 30 km
Census of India, 1991, District Census Hand Book, Orissa
Block 1991
18 Percentage of villages with health services within 10 km
Census of India, 1991, District Census Hand Book, Orissa
Block 1991
19 Percentage of villages connected by metal road
Census of India, 1991, District Census Hand Book, Orissa
Block 1991
20 Percentage of landless agricultural labour
Census of India, 1991, District Census Hand Book, Orissa
Block 1991