Levels, Patterns and Determinants of Food Insecurity in...

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“Levels, Patterns and Determinants of Food Insecurity in Urban India”

Author: Protap Mukherjee

Affiliation: Jawaharlal Nehru University (JNU), Centre for the Study of Regional

Development, School of Social Sciences

Abstract: Urbanization is becoming the most dominant demographic process in India and,

as urban populations grow, poverty, food insecurity and malnutrition will increase

significantly. The first objective of this paper is to construct an overall urban food insecurity

index for major states in India. The second objective is to examine levels and determinants of

urban food insecurity at the household level using bivariate and multivariate analyses.

Findings show that there is a regional disparity in overall urban food insecurity among the

states and livelihood and small household size have come out as important determinants in

explaining nutritional security.

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INTRODUCTION:

According to the 2001 Indian census, approximately 28 percent of urban population lives in

urban areas, though in absolute terms this population of 290 million people does not equally

share that the benefits of urbanization that the top deciles of the population enjoys. The

majority of the urban population are living in slums and squatter settlements as a result of an

improper urbanization process, which is itself rooted in distress-induced migration towards

urban areas. Slums and poor households in urban areas are characterized by unsanitary living

conditions and high food insecurity.

Urbanization is becoming the most dominant demographic process in India and, like

all other developing countries, the urban population of India is also expected to grow rapidly

in coming decades. As urban populations grow, poverty, food insecurity and malnutrition will

increase significantly and poor will be severely affected.

Nutritional status in urban areas is appalling. Infant and child mortality are high and

more differences in infant mortality have been observed between richer and poorer people in

urban areas. Child and women‟s health are deteriorating. Many of these problems in poor

urban households are caused by a lack of access to water, sewage, adequate levels of hygiene,

and contamination of water and food (IFPRI Discussion Paper, 1998).

Urban food insecurity is complex in nature; it depends not only on the buying

capacities of urban denizens, but also takes into account improved housing, healthy and

hygienic living conditions, education and less gender discriminations in and outside urban

households. Moreover, higher birth rates among the poor in India also add more vulnerability.

It is important to consider urban food insecurity to be a growing problem demanding

greater attention, where most poor, food insecure people in developing countries currently

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live. Sustainable approaches are needed to improve urban-based programmes in development

settings (WFP, 2002).

OBJECTIVES: In the present paper, urban food insecurity scenarios have been examined in

two perspectives, one is a macro level analysis of food insecurity and the other relates to

household food insecurity. The general objective of this paper deals with the first perspective

- to study the levels and patterns of food insecurity at the state level by analyzing levels and

patterns of six different indices: food affordability index, livelihood access index, housing

index, discrimination index, sanitation and health index and nutritional outcome index. Each

of these indices has been computed on the basis of appropriate indicators. Finally, a

composite index has been developed to portray the food insecurity scenario in urban India.

Second objective of this paper deals with concept of household food insecurity and its

determinants in urban settings. The specific objectives under this perspective are 1) to assess

the level of nutritional status of women in urban India, 2) to analyze the effect of household

characteristic and demographic factors on the level of nutritional status and 3) to examine the

role of women, in terms of their education level, control over decision-making and mass

media exposure, in nutritional status.

DATA: In the present study, data have been taken from many sources. All indicators which

are used in this paper relate to urban India only. For the general objective, i.e., to study the

patterns of urban food insecurity at state level, data have been obtained from National Sample

Survey Organization-61st Round (2004-05), the National Family Health Survey-3 (2005-06),

Sample Registration System (2004 and 2007), and Planning Commission (2005). For the

specific objective, i.e., to examine the level and determinants of urban household food

insecurity, individual level women data file from National Family Health Survey (NFHS-3,

2005-06) have been used.

METHODOLOGY:

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For General Objective: To study the levels and spatial patterns of urban food insecurity,

seventeen major states of India have been selected. For state level analysis, the Overall Urban

Food Insecurity Index 2005 has been developed on the basis of six dimensions of urban food

insecurity (MSSRF and WFP, 2002). These dimensions are food affordability, livelihood

access, housing, gender discrimination, sanitation and health and nutritional outcome. Six

separate indices have been created to study these six dimensions. Table-1 is placed below to

show the indicators under each dimension and how together these indices relate to overall

urban food insecurity.

Table-1: Framework for Overall Urban Food Insecurity Index 2005

Objective Dimension-index Indicators Data Source

Overall Urban Food Insecurity Index 2005

Food Affordability Index Percentage of households reporting food grains (rice + wheat) consumptions from PDS (2004-05) NSSO, 61st Round, 2004-05

Average per day calorie intake (Kcal) (2004-05) ,,

Livelihood Access Index

Percentage of population below poverty level (2004-05) NSSO, 61st Round and Planning Commission, 2005

Percentage of casual labour in principal and subsidiary works (2004-05) NSSO, 61st Round, 2004-05

Percentage of urban illiteracy (2004-05 ,,

Housing Index

Average household size (2004) SRS, 2004

Percentage of households living in a kachha houses (2005-06) NFHS-3, 2005-06

Percentage of households living in a semi-pucca houses (2005-06) ,,

Gender Discrimination Index

sex-ratio (number of women per 1,000 men) (2005-06) ,,

Average daily male-female wage differential in casual works (2004-05) NSSO, 61st Round, 2004-05

Sanitation & Health Index

Percentage of households with proper drainage (2004) SRS, 2004

Percentage of households with garbage disposal facilities (2004) SRS, 2004

Percentage of households with no toilet or poor toilet (2004) SRS, 2004

Percentage of households with not-improved drinking water (2005-06) NFHS-3, 2005-06

Nutritional Outcome Index

Infant mortality rate (2006) SRS, 2007

Percentage of underweight children (below 3 years) (2005-06) NFHS-3, 2005-06 Percentage of ever-married women (15-49) suffering from anaemia (2005-06) NFHS-3, 2005-06

Source: MSSRF and WFP, 2002 and personal research

As clear from the above table, all seventeen indicators used for creating overall urban

food insecurity index are first categorized into six dimensions. Each indicator in the study has

been converted into an individual index to make it scale free. Maximum indicators have been

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chosen in such a manner that larger values represent worse situations. The following formula

has been used to calculate the relative scores for each indicator where „0‟ represents the best

value and „1‟ represents the worst value.

Xi - Xmin

Vi = ---------------------

Xmax – Xmin

To make all indices unidirectional („0‟ best and „1‟ worst), the above formula has

been modified a little for some indicators (food availability, calorie intake, sex-ratio, proper

drainage and garbage disposal facilities) where larger value represents better situations. The

formula used for these indicators is as follows:

Xmax – Xi

Vi = ---------------------

Xmax – Xmin

Where, Xi = Observed value for a particular indicator in a state

Xmin = the minimum value for a particular indicator

Xmax = the maximum value for a particular indicator

Vi = Individual index

The six dimension indices have been computed using the following formula:

Σ Vi

DI = ---------------

n

Where, Vi = Individual index,

n = = total numbers of variables used for calculating index,

DI = Dimension Index

The overall urban food insecurity index has been computed on the basis of the

following formula: ∑ DI / total number of dimension indices.

For Specific Objective: For studying urban household food insecurity, NFHS-3 (2005-06)

data have been used. Only urban data have been utilized from all India women data file.

Household food insecurity in urban setup has been examined in the context of the nutritional

status of women aged 15-49. A sample of 49,813 women from urban India has been studied

in this objective. The level of anaemia among women has been examined by different

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household and demographic variables. In the present study, household characteristics include

size of the household, sex and age of the household head, house ownership, wealth index and

religion whereas demographic variables include age of the women and total children ever

born. Women‟s role has also been judged by education, working status, mass-media

exposures and decision making abilities. Simple bivariate analyses and one multivariate

logistic regression analysis have been carried for the first objective.

FINDINGS

Levels and Patterns of Urban Food Insecurity at State Level

The relative position of each state out of seventeen major states in India has been studied by

examining individual index, dimension indices and overall urban food insecurity index. All

these indicators are characteristics of vulnerable populations in urban India. It has been found

that the relative position of a single state is not same for all indicators. And there is a

variation in state-wise performances across a single index. For the purpose of sustainable

urbanization, it is imperative to study all major dimensions of urban food insecurity.

Food Affordability Index: As this index is based on average consumptions of foodgrains

from public distribution systems (PDS) and average daily calorie intake, it represents the

“availability and accessibility” dimensions of food insecurity concept. It can be seen from

Table-2 that consumption of foodgrains from PDS is not same in all states. There is a great

disparity in consumptions of foodgrains from PDS among urban households across the states

as clearly envisaged by standard deviation for this indicator (16.1 percent) which is almost

same as national average (18.9 percent). Tamil Nadu is the highest consumer (58 percent)

whereas urban Punjab comes out as a lowest consumer (less than 1 percent) from PDS.

Regarding daily calorie intake index, Maharashtra is worst and Jharkhand emerges as best. In

terms of the overall food affordability index, southern states perform well. Tamil Nadu is best

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state followed by Jharkhand, Kerala and Andhra Pradesh, whereas Maharashtra is the worst

state followed by Haryana, West Bengal and Rajasthan.

Table-2: Food affordability Index in urban India

Major States

Food Affordability Index in Urban India

% of Households Reporting Food

grains (rice + wheat)

Consumptions from PDS (2004-05)

PDS Food grains Consumption

Index (2004-05)

Average Daily Calorie Intake (Kcal)

(2004-05)

Calorie Intake Index

(2004-05)

Food Affordability

Index (2005)

Rank (2005)

Andhra Pradesh 31.8 0.46 2,449 0.75 0.606 4

Assam 2.6 0.97 2,593 0.56 0.763 11

Bihar 2.2 0.97 2,683 0.44 0.706 7

Chhattisgarh 18.6 0.69 2,550 0.62 0.653 6

Gujarat 14.0 0.77 2,436 0.77 0.768 13

Haryana 5.2 0.92 2,487 0.70 0.811 16

Jharkhand 4.8 0.93 3,013 0.00 0.464 2

Karnataka 35.6 0.40 2,385 0.84 0.615 5

Kerala 35.4 0.40 2,534 0.64 0.518 3

Madhya Pradesh 19.0 0.68 2,397 0.82 0.751 10

Maharashtra 12.9 0.79 2,261 1.00 0.894 17

Orissa 6.8 0.89 2,596 0.55 0.724 8

Punjab 0.7 1.00 2,614 0.53 0.765 12

Rajasthan 2.1 0.98 2,586 0.57 0.772 14

Tamil Nadu 58.4 0.00 2,394 0.82 0.412 1

Uttar Pradesh 4.7 0.93 2,598 0.55 0.741 9

West Bengal 8.9 0.86 2,467 0.73 0.792 15

India 18.9 0.74 2,475 0.64 0.692 Standard Deviation 16.1 0.28 164 0.22 0.130 Source: National Sample Survey Organization-61

st Round, 2004-05

Livelihood Access Index: Urban livelihood access in the present paper has been

conceptualized on the basis of amalgamation of the urban population living below poverty

line, percent casual labour in urban areas and urban illiteracy. Whereas population below

poverty line and percent casual labours directly point at vulnerability in urban areas, urban

illiteracy can be taken as an indirect yet strong dynamic measure of livelihood, as literacy is

positively related to employment options and hence with better livelihood. Orissa, with 46

percent of its urban population living below poverty line, ranks lowest whereas Punjab stands

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as best (only 8 percent). Even the national average for percentage of population living below

poverty line is distinctly high - almost 28 percent.

Table-3: Livelihood Access in Urban India

Livelihood Access Index in Urban India

Major States

% of Population

Below Poverty

Level (2004-05)

Population Below

Poverty Level Index (2004-05)

% of Casual Labour in Principal

and Subsidiary

works (2004-05)

Casual Labour Index

(2004-05)

% of Urban

Illiteracy (2004-05)

Urban Illiteracy

Index (2004-05)

LIVELIHOOD ACCESS INDEX (2005)

RANK (2005)

Andhra Pradesh 15.8 0.19 19.4 0.52 30.4 0.73 0.482 10

Assam 19.7 0.30 12.6 0.22 17.7 0.15 0.221 2

Bihar 41.4 0.87 17.9 0.45 31.6 0.79 0.702 16

Chhattisgarh 40.9 0.86 20.8 0.58 24.1 0.44 0.627 14

Gujarat 16.8 0.22 13.5 0.26 20.5 0.28 0.252 4

Haryana 14.0 0.15 7.8 0.00 26.2 0.54 0.229 3

Jharkhand 40.3 0.84 18.3 0.47 23.5 0.42 0.575 12

Karnataka 25.0 0.44 19.3 0.52 24.1 0.44 0.465 9

Kerala 15.0 0.17 30.1 1.00 14.4 0.00 0.391 7

Madhya Pradesh 38.3 0.79 15.4 0.34 27.8 0.61 0.580 13

Maharashtra 30.7 0.59 15.5 0.35 20.2 0.26 0.399 8

Orissa 46.4 1.00 20.0 0.55 27.9 0.62 0.721 17

Punjab 8.4 0.00 7.9 0.00 22.9 0.39 0.131 1

Rajasthan 22.1 0.36 11.4 0.16 36.3 1.00 0.507 11

Tamil Nadu 22.5 0.37 16.1 0.37 19.4 0.23 0.324 5

Uttar Pradesh 39.6 0.82 11.1 0.15 34.5 0.92 0.629 15

West Bengal 24.7 0.43 16.6 0.39 19.5 0.23 0.352 6

India 27.5 0.49 15.0 0.37 24.8 0.47 0.446 Standard Deviation 11.9 0.31 5.4 0.24 6.1 0.28 0.179

Source: National Sample Survey Organization-61st

Round, 2004-05 and Planning Commission, 2005

It is interesting to note that Kerala comes out as the worst state regarding percentage

of casual labour whereas its performance in terms of literacy is the best among all major

states. Concerning the overall livelihood access index, the best performing state is Punjab,

followed by Assam, and the worst performing state is Orissa, followed by Bihar and Uttar

Pradesh.

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Housing Index: For computation of the housing index, average household size has been

considered along with percentage of urban population living in kachha or semi-pucca houses.

It can be understood that if household size is greater and means of livelihood is lower, then

this can lead to a situation of food insecurity in the households.

Table-4: Housing index in urban India

Housing Index in Urban India

Major States

Average Household

Size (2004)

Average Household Size Index

(2004)

% of Households Living in a

Kachha Houses

(2005-06)

kachha Houses Index

(2005-06)

% of Households Living in a

Semi-pucca Houses

(2005-06)

Semi-pucca

Houses Index

(2005-06)

HOUSING INDEX (2005)

RANK (2005)

Andhra Pradesh 4.5 0.18 4.0 0.38 15.1 0.22 0.256 10

Assam 4.5 0.18 2.9 0.27 46.0 1.00 0.482 12

Bihar 5.5 0.76 10.1 0.96 27.4 0.53 0.751 17

Chhattisgarh 5.5 0.76 1.9 0.17 30.6 0.61 0.516 13

Gujarat 4.7 0.29 0.3 0.02 7.0 0.01 0.108 4

Haryana 4.9 0.41 0.2 0.01 11.1 0.11 0.179 6

Jharkhand 5.0 0.47 0.1 0.00 19.7 0.33 0.268 11

Karnataka 4.6 0.24 1.8 0.16 17.2 0.27 0.223 8

Kerala 4.5 0.18 1.2 0.11 6.6 0.00 0.094 2

Madhya Pradesh 5.1 0.53 5.7 0.54 25.8 0.49 0.518 14

Maharashtra 4.6 0.24 0.1 0.00 10.6 0.10 0.112 5

Orissa 4.8 0.35 10.5 1.00 24.8 0.46 0.605 16

Punjab 4.4 0.12 0.4 0.03 6.7 0.00 0.050 1

Rajasthan 5.1 0.53 1.5 0.13 10.4 0.10 0.253 9

Tamil Nadu 4.2 0.00 4.7 0.44 13.4 0.17 0.205 7

Uttar Pradesh 5.9 1.00 2.6 0.24 21.8 0.39 0.542 15

West Bengal 4.2 0.00 1.0 0.09 15.1 0.22 0.101 3


Source: Sample Registration System, 2004 and National Family Health Survey-3, 2005-06

From Table-4, it can be seen that the average household size is not equal across the

states. Urban Tamil Nadu and urban West Bengal have the lowest household size (4) and

urban Uttar Pradesh has the highest (6). Regarding percentage of population living in kachha

houses, Maharashtra and Jharkhand (both 0.1 percent urban population) rank best and Orissa

(10 percent) ranks in the worst position. In terms of population living in semi-pucca houses,

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Assam is the worst state, where the best position is obtained by Kerala and Punjab. But Bihar

and Punjab come out as the worst state and best state respectively considering the overall

housing index.

Gender Discrimination Index: Earlier studies show that there is a gender disparity in

household food insecurity and that women are more vulnerable. Considering this, a

discrimination index has been constructed on the basis of gender.

Table-5: Gender discrimination index in urban India

Discrimination Index in Urban India

Major States Sex Ratio, All Ages

(2005-06)

Sex Ratio Index

(2005-06)

Average Daily Male-Female Wage

Differential in Casual Works

(2004-05)

Average Daily Wage Differential

Index (2004-05)

DISCRIMINATION INDEX (2005)

RANK (2005)

Andhra Pradesh 1027 0.36 28.4 0.57 0.468 3

Assam 914 0.70 17.7 0.46 0.580 10

Bihar 947 0.60 -27.3 0.00 0.300 1

Chhattisgarh 984 0.49 15.2 0.44 0.464 2

Gujarat 890 0.77 37.1 0.66 0.715 15

Haryana 837 0.92 32.4 0.61 0.768 16

Jharkhand 936 0.63 4.7 0.33 0.480 4

Karnataka 990 0.47 34.5 0.63 0.554 7

Kerala 1151 0.00 70.0 1.00 0.500 6

Madhya Pradesh 886 0.78 9.5 0.38 0.579 9

Maharashtra 928 0.66 40.5 0.70 0.676 14

Orissa 937 0.63 21.4 0.50 0.565 8

Punjab 811 1.00 37.5 0.67 0.833 17

Rajasthan 889 0.77 20.9 0.49 0.633 13

Tamil Nadu 1042 0.32 35.5 0.65 0.483 5

Uttar Pradesh 915 0.69 25.4 0.54 0.618 12

West Bengal 944 0.61 31.1 0.60 0.604 11

India 939 0.61 31.2 0.54 0.578 Standard Deviation 80 0.24 20.0 0.21 0.128 Source: National Family Health Survey-3 (2005-06) and Sample Registration System, 2004

State level differentials in gender discrimination in India can be understood by

looking at Table-5. Only three southern states (Andhra Pradesh, Kerala and Tami Nadu) in

India have more females than males, whereas the situation is reverse for all other major

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states. Punjab (811), followed by Haryana (837) has the highest adverse sex ratio in the

country. Similarly, there is a wide wage-gap between males and females who work as casual

labours. Interestingly, women in Bihar are earning more in casual work than their male

counterparts, whereas the maximum wage-differential has been found in Kerala. Regarding

the overall gender discrimination index, Bihar comes out as best and Punjab ranks in the

worst position.

Sanitation and Health Index: Sanitation, along with health awareness, is regarded as the

utilization part of food insecurity concept. The spatial differentials in the levels of sanitation

and health index are shown in Table-6.

Table-6: Sanitation and health index in urban India

Sanitation and Health Index in Urban India

Major States

% of Households with Proper

Drainage Facilities

(2004)

Proper Drainage

Index (2004)

% of Households

with No Toilet or

Poor Toilet (2004)

Poor Toilet

Facilities Index (2004)

% of Households

with Not-improved Drinking

Water (2005-06)

Not-improved Drinking Water

Facilities Index

(2005-06)

SANITATION & HEALTH

INDEX (2005)

RANK (2005)

Andhra Pradesh 43.6 0.33 11.5 0.33 0.4 0.02 0.225 5

Assam 22.4 0.74 6.6 0.19 14.5 0.64 0.523 13

Bihar 45.4 0.30 25.9 0.74 3.2 0.14 0.392 10

Chhattisgarh 15.6 0.87 35.1 1.00 6.9 0.30 0.725 16

Gujarat 49.3 0.22 8.3 0.24 2.5 0.11 0.189 3

Haryana 41.8 0.37 3.9 0.11 1.4 0.06 0.179 2

Jharkhand 36.4 0.47 24.5 0.70 11.4 0.50 0.557 14

Karnataka 60.7 0.00 11.3 0.32 11.8 0.52 0.281 8

Kerala 9.0 1.00 0.0 0.00 22.7 1.00 0.667 15

Madhya Pradesh 38.3 0.43 22.2 0.63 8.5 0.37 0.480 11

Maharashtra 52.8 0.15 16.6 0.47 0.7 0.03 0.219 4

Orissa 23.5 0.72 34.5 0.98 15.9 0.70 0.801 17

Punjab 58.0 0.05 8.2 0.23 0.0 0.00 0.095 1

Rajasthan 30.0 0.59 14.0 0.40 1.0 0.04 0.346 9

Tamil Nadu 25.1 0.69 20.4 0.58 6.3 0.28 0.516 12

Uttar Pradesh 53.3 0.14 18.7 0.53 1.4 0.06 0.246 6

West Bengal 37.6 0.45 10.1 0.29 2.1 0.09 0.276 7


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It is evident from the above table that the performance of states regarding the overall

sanitation and health index widely varies. It has been found that there are states in India

which are not performing well regarding the supply of improved drinking water or the

provision of toilet facilities to all urban households. The percentage of urban households with

proper drainage facilities significantly varies from 61 percent (Karnataka) to only 9 percent

(Kerala). Although, as the data reveals, the percentage of urban households having no toilet

or poor toilet facilities is least in Kerala, the same state has come out as the worst performer

in terms of improved drinking water. While considering overall sanitation and health index,

Punjab is in the best position, followed by Haryana, and Orissa is the worst state, followed by

Chhattisgarh.

Nutritional Outcome Index: The indicators used for constructing this index and the overall

index itself can be considered as the most helpful in understanding the food insecurity

scenario in urban India as this index gives direct measures of nutritional and health status of

population which are, again, to a large extent dependent on the food security situation in a

given area.

Table-7: Nutritional outcome index in urban India

Nutritional Outcome Index in Urban India

Major States

Infant Mortality

Rate (2006)

Infant Mortality

Rate Index (2006)

% of Underweight

Children (Below 3

Years) (2005-06)

Underweight Children

Index (2005-06)

% of Ever-married

Women (15-49) Suffering

From Anaemia (2005-06)

Anaemic Women

Index (2005-06)

NUTRITIONAL OUTCOME

INDEX (2005)

RANK (2005)

Andhra Pradesh 38 0.63 29.1 0.24 58.4 0.72 0.531 7

Assam 42 0.73 34.1 0.40 66.3 0.93 0.689 14

Bihar 45 0.80 51.5 0.96 68.8 1.00 0.921 17

Chhattisgarh 50 0.93 38.9 0.56 50.3 0.49 0.659 11

Gujarat 37 0.61 42.7 0.68 50.5 0.50 0.595 9

Haryana 45 0.80 42.1 0.66 55.6 0.64 0.700 15

Jharkhand 32 0.49 43.3 0.70 59.4 0.74 0.642 10

Karnataka 36 0.59 33.8 0.39 46.7 0.39 0.458 4

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Kerala 12 0.00 22.5 0.03 32.3 0.00 0.011 1

Madhya Pradesh 52 0.98 52.8 1.00 48.3 0.44 0.805 16

Maharashtra 26 0.34 34.8 0.42 46.6 0.39 0.386 3

Orissa 53 1.00 33.3 0.38 56.4 0.66 0.679 13

Punjab 36 0.59 21.5 0.00 40.0 0.21 0.265 2

Rajasthan 41 0.71 36.3 0.47 48.0 0.43 0.537 8

Tamil Nadu 33 0.51 31.3 0.31 52.6 0.56 0.460 5

Uttar Pradesh 53 1.00 37.9 0.52 50.7 0.50 0.676 12

West Bengal 29 0.41 30.0 0.27 59.0 0.73 0.473 6

India 39 0.65 36.4 0.47 51.5 0.55 0.558 Standard Deviation 10.8 0.26 8.6 0.27 9.0 0.25 0.212


Regarding infant mortality rate, Kerala is the best and Orissa is found to be the worst

state in India. Fifty-three percent of children below three years of age in Madhya Pradesh are

underweight while the percentage of underweight children in total child population (children

below three years) is lowest (22 percent) in Punjab. Data reveal that 69 percent of urban ever-

married women in Bihar are suffering from anaemia. The lowest percentage of anaemic

women among states has been found in Kerala (32 percent). In terms of the overall

nutritional outcome index, Kerala, Punjab and Maharashtra perform well, whereas Bihar,

Madhya Pradesh and Haryana rank in the worst positions.

Overall Urban Food Insecurity Index 2005: An overall urban food insecurity index for the

year 2005 has been constructed on the basis of six other indices, as food insecurity issue in

urban areas is a complex one and a holistic approach is needed to examine it at a macro level.

Urban food insecurity or vulnerable populations that may become food insecure in future can

not be determined by studying only a few indicators. Food insecurity in urban India is a

dynamic concern and there are many issues that reduce or accelerate the degree of

vulnerability among an urban population.

An understanding of food insecurity depends on the understanding its components –

availability, accessibility and utilization of food. The six indices selected to construct the

composite index are well representative of components in the food insecurity study. Gender

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discrimination has been included in constructing the composite index because women are a

vulnerable population and face more food insecurity even at the household level.

Table-8 represents the positions of major states in terms of overall urban food

insecurity. It has been found that urban areas in Punjab come out as the least food insecure in

India, followed by Kerala and Tamil Nadu. On the other hand, urban populations in Orissa

are found to be the most food insecure, followed by Bihar and Madhya Pradesh. Urban areas

in Maharashtra, Haryana and Jharkhand are medium food insecure considering the relative

positions of these states among total 17 major states.

Table-8: Overall urban food insecurity index 2005

Composite Index of Urban Food Insecurity, 2005

Major States Food

Affordability Index


Housing index

Gender Discrimination

Index

Sanitation and Health

Index

Nutritional Outcome

Index

URBAN FOOD

INSECURITY INDEX 2005

RANK

Andhra Pradesh 0.606 0.482 0.256 0.468 0.228 0.531 0.428 4

Assam 0.763 0.221 0.482 0.580 0.617 0.689 0.559 12

Bihar 0.706 0.702 0.751 0.300 0.438 0.921 0.637 16

Chhattisgarh 0.653 0.627 0.516 0.464 0.635 0.659 0.592 14

Gujarat 0.768 0.252 0.108 0.715 0.142 0.595 0.430 5

Haryana 0.811 0.229 0.179 0.768 0.230 0.700 0.486 9

Jharkhand 0.464 0.575 0.268 0.480 0.563 0.642 0.499 10

Karnataka 0.615 0.465 0.223 0.554 0.281 0.458 0.433 6

Kerala 0.518 0.391 0.094 0.500 0.750 0.011 0.377 2

Madhya Pradesh 0.751 0.580 0.518 0.579 0.461 0.805 0.616 15

Maharashtra 0.894 0.399 0.112 0.676 0.245 0.386 0.452 8

Orissa 0.724 0.721 0.605 0.565 0.718 0.679 0.669 17

Punjab 0.765 0.131 0.050 0.833 0.118 0.265 0.360 1

Rajasthan 0.772 0.507 0.253 0.633 0.333 0.537 0.506 11

Tamil Nadu 0.412 0.324 0.205 0.483 0.404 0.460 0.381 3

Uttar Pradesh 0.741 0.629 0.542 0.618 0.244 0.676 0.575 13

West Bengal 0.792 0.352 0.101 0.604 0.324 0.473 0.441 7

India 0.692 0.446 0.310 0.578 0.396 0.558 0.496 -

Minimum 0.412 0.131 0.050 0.128 0.118 0.011 0.360 -

Maximum 0.894 0.721 0.751 0.833 0.750 0.921 0.669 -

Standard Deviation 0.130 0.179 0.214 0.128 0.199 0.212 0.096 -

Source: Personal calculations of indices based on sources mentioned earlier

15

As evident from the above composite index, most food insecure states in the above

table are those states which are considered as Empowered Action Group (EAG) states in

India. EAG states are states whose performances are poor in terms demographic and

economic context. In fact, except for Assam, which ranked in the 12th

position, all states

starting from rank 17 to rank 10, fall under EAG states category.

Interestingly, Punjab, which came out as the least food insecure state, performed

worst in terms of the discrimination index. The same is true in case of the urban population in

Kerala, which is the second least food insecure state in India despite having ranked low

regarding sanitation and health index, and especially low regarding proper drainage systems

and improved drinking water facilities. In case of urban Orissa, its performance is adequate in

food affordability and gender discrimination, but comes out as the most food insecure state.

Table-9: Correlation Matrix

Index Food

Affordability Index


Housing index

Discrimination Index

Sanitation and Health

Index

Nutritional Outcome

Index

URBAN FOOD

INSECURITY INDEX

Food Affordability Index 1.00 Livelihood Access Index 0.31 1.00

Housing index 0.28 0.79 ** 1.00 Gender Discrimination Index 0.82 ** 0.04 -0.02 1.00

Sanitation and Health Index 0.12 060 ** 0.59 ** 0.03 1.00 Nutritional Outcome Index 0.55 * 0.66 ** 0.79 ** 0.31 0.35 1.00

URBAN FOOD INSECURITY INDEX o.69 ** 0.76 ** 0.77 ** 0.40 0.56 ** 0.80 ** 1.00 ** Significant at 1 % level and * significant at 5 % level

It has been found that the livelihood access and housing indices are significantly

correlated with urban food insecurity. The nutritional outcome index, which is also an

outcome indicator in food insecurity study, was significantly associated with the housing and

livelihood index. And the strong correlation between gender discrimination index and food

affordability index raise the issue that women are being discriminated against in terms of

food intake.

16

These findings explain that magnitude of vulnerability in food insecurity in urban

India resulted from many factors which are intermingling with each other. And sustainable

solutions to reduce vulnerability in urban India also lie in minimizing the effects of all

individual factors account for it. There is a need to improve livelihood options for the poor as

well as providing better housing facilities in urban areas. Appropriate policies, especially for

urban slums and other vulnerable groups should be implemented.

Levels, Patterns and Determinants of Urban Food Insecurity at Household Level

Earlier paragraphs revealed the levels of urban food insecurity and its dimensions at the state

level. We have seen that the food insecurity situation is not homogeneous across the states;

all states are not equally vulnerable. Sustainable urban planning is necessary to improve the

conditions of food insecure urban populations and hence it requires more insights about

determinants of food insecurity at household level. In this objective, an attempt has been

made to study urban food insecurity at micro level, i.e., at household level.

In the present analyses, only women from urban India have been considered. As

women are found to be the more vulnerable and discriminated against within the households,

women‟s nutritional status (prevalence of anaemia) has been taken as a proxy for studying the

level of food insecurity. I try to examine the prevalence of anaemia by different household

characteristics and also by women‟s status in the household.

Prevalence of anaemia by Different household characteristics: Table-10 represents

differentials in the percentage of urban women suffering from three anaemia levels – severe,

moderate and mild, by different household conditions. At national level, 49 percent of all

urban women suffer from some degree of anaemia, with 13.3 percent suffering from severe to

moderate anaemia. It is found that prevalence of any type of anaemia is much higher among

those women who belonged to large households. Prevalence of any anaemia is marginally

less where the head of the household is female.

17

Fifty-six percent of women from the households where the age of the household head

is below 26 are suffering from anaemia, whereas this percentage is 48 in case of those

household where the age of the head is more than 40. Prevalence of anaemia is higher among

the women who don‟t have their own houses. The wealth index used here can be taken as the

livelihood index used in the previous objectives. Sixty-nine percent women from the poorest

households have anaemia whereas 45 percent women from the richest households are

afflicted, with 34 percent suffering only mild anaemia. The impact of wealth on the

prevalence of anaemia can be clear from studying the differential in severe and moderate

anaemia. Whereas almost 25 percent from poorest households have severe to moderate

anaemia, only 11 percent women from richest families are suffering from the same. There are

also differentials in anaemia levels by religion and it has been found that the prevalence of

anaemia is much higher among Hindu or Muslim households.

Table-10: Prevalence of anaemia among women aged 15-49 in urban India

Household Characteristics Anaemia level Percentage of

women with any level of anaemia

Total sampled women Severe Moderate Mild

Size of the household ½ 1.7 12.0 34.2 47.9 2,048

3-5 1.3 11.8 35.3 48.3 26,257

6 or more 1.3 12.4 36.1 49.8 21,508

Sex of Household Head Male 1.3 12.1 35.6 49.0 42,940

Female 1.4 11.5 35.8 48.7 6,873

Age of the household head 25 and less 2.0 17.0 36.8 55.8 1,477

26-40 1.3 12.4 36.8 50.5 16,222

41 and above 1.3 11.6 34.9 47.9 32,114

Whether household owns this or another house Yes 1.2 11.7 35.3 48.3 37,826

No 1.6 13.0 36.5 51.1 11,987

Wealth index Poorest 3.5 21.2 43.7 68.5 8,21

Poorer 1.7 17.2 40.0 58.9 2,243

Middle 2.1 14.9 38.1 55.1 5,914

Richer 1.6 13.3 36.5 51.4 14,264

18

Richest 0.9 10.0 33.9 44.9 26,571

Religion Hindu 1.4 12.5 36.3 50.2 36,034

Muslim 1.1 12.2 36.2 49.5 8,006

Christian 0.8 9.3 29.3 39.4 3,,273

Others 1.4 9.2 31.2 41.8 2500

All India (urban) 1.3 12.0 35.6 49.0 49,813 Source: personal analyses from women data file, NFHS-3 (2005-06)

Demography and the Status of Women in the Prevalence of Anaemia: Table-11 represents

prevalence of anaemia among women by demographic and status variables. It has been found

that the prevalence is higher among women in age-group of below twenty-five. Prevalence is

also higher among women having more than two children than women having two or less

than two children, and the level of women‟s education has an impact on the prevalence of

anaemia. Seventeen percent women from non-literate backgrounds are suffering from severe

to moderate anaemia compared to 10 percent of women with higher educational

achievements. Women who are exposed to mass media are less anaemic and prevalence rates

have been found to be marginally higher among women who don‟t have a final say about

daily household purchases.

Table-11: Prevalence of anaemia among women in urban India by various demographic

characteristics and status of women

Demographic and Status Variables

Percentage anaemic

Severely/ Moderately

Anaemic Mildly Anaemic

Age of the woman

Less than 25 14.3 35.6

25 – 40 12.6 35.8

41 and above 13.4 34.8

Total children ever born

less than or equal to 2 12.8 35.1

more than 2 14.7 36.8

Educational attainment

No education 16.7 37.7

Primary 16.0 36.7

Secondary 12.8 35.4

Higher 9.6 33.1

Current working status of the woman

19

Non-working 13.3 35.7

Working 13.4 35.4

Mass media exposure

Not exposed 17.5 37.8

Exposed 12.9 35.3

Final say on daily household purchase

Alone or jointly with husband 13.1 36.0

Others 13.6 35.2

Source: personal analyses from women data file, NFHS-3 (2005-06)

Determinants of Anaemia among Women: A Binary Logistic Regression analysis has been

carried out for predicting the role of households, demographic and other variables on the

incidence of anaemia. Women with no anaemia have been assigned value „0‟and those with it

have been assigned value „1‟. Table-12 represents the results of binary logistic regression.

It has been found that women from bigger households (sic or more) are 15 percent

more likely to be anaemic than women from household with one to two members. The

likelihood of having anaemia also decreases as the age of the household head increases. The

wealth index has come out as the most significant predicting variable in explaining anaemia

among urban women. As wealth index increases, the likelihood of having anaemia decreases.

Rich urban women are 43 to 56 percent less likely to have anaemia. The role of women‟s

education in predicting prevalence of anaemia in urban settings is significant only in case of

those women who have more than secondary education. These women have 15 percent less

chance to have anaemia in comparison to their illiterate counterparts.

The likelihood of getting anaemia is found to be lower in women in the age-group of

twenty-six to forty. The likelihood is also low among women with a small number of

children. Though it is not statistically significant, women with working status are four times

less likely to have anaemia.

All the above findings about women nutritional status at household level

confirm the results found in the state level analyses of food insecurity. Even at the household

level, controlling for other variables, wealth (livelihood) has come out as an important

20

determinant. Other factors like household size, number of children born, and women‟s

education levels also play important roles in determining nutritional status, which as

mentioned earlier can be taken as a proxy for food insecurity.

Better livelihoods will give urban women ample scopes to be educated, which

in turn will generate awareness about the necessity of small family norms along with

knowledge of sanitation and personal hygiene and these together will be competent to bring

down the degree of vulnerability in food insecurity issues in urban India.

21

Table-12: Binary logistic regression analysis for predicting incidence of anaemia among

women aged 15-49 in urban India

Indicators Exp(B) Significance level

Size of the household

1- 2 ®

3-5 1.092 0.067

6 or more 1.155 * 0.004

Age of the household head

25 and less®

26-40 0.883 0.030

41 and above 0.846 * 0.003

Whether household owns this or another house

Yes®

No 1.098 ** 0.000

Wealth index

Poorest®

Poorer 0.680 ** 0.000

Middle 0.593 ** 0.000

Richer 0.527 ** 0.000

Richest 0.435 ** 0.000

Religion Hindu 1.321 ** 0.000

Muslim 1.173 ** 0.001

Christian 0.870 0.011

Others®

Age of the woman

Less than 25®

25 – 40 0.914 ** 0.000

41 and above 0.927 0.029

Total children ever born

less than or equal to 2®

more than 2 1.080 * 0.002

Educational attainment of the woman

No education®

Primary 1.014 0.684

Secondary 0.954 0.100

Higher 0.849 ** 0.000

Current working status of the woman

Non-working®

Working 0.962 0.062 Dependent variable: Anaemic = 1, Non-anaemic=0. ** Significant at 1% level, * at 5% level

®Reference category; total cases in the analysis = 49,713

22

CONCLUSIONS AND POLICY IMPLICATIONS:

The present paper is centred on food insecurity issues in urban India, at both state and

household levels. From the state level point of view, degree of food insecurity differs in

urban areas. Some states in the country are less food insecure whereas urban populations in

the other states are highly disadvantaged and vulnerable. A closer looks at the well-

performing states show that they are less food insecure, urban population living these states

are relatively well-off, they enjoy improved housing, having the benefits from better

livelihood conditions as well as knowledge and utilizations of sanitation and health are also

enhanced.

Findings from household level analyses also validate the reasons of disparity in urban

settings among different states. No doubt that an urban household needs to provide with

better livelihood to maintain healthy nutritional status, but even there is a need to minimize

the household sizes and birth rates. Along with poor living conditions, the vulnerability in

slums and poor households in cities of India is also embedded in larger families (Brockerhoff,

2000). Moreover, to reduce the disparity in the households, women need to be educated,

must make their own decisions, and should be permitted to work (Engle, 2000).

The reasons for vulnerability in urban areas are deepened in households and all

policies should address these issues and need to be implemented properly. States should call

for proper actions to improved livelihood conditions of food insecure urban areas and effects

of actions should be penetrating in households. To bring a sustainable approach in

urbanization process, there is a need to include all dimensions that relate to food insecurity

scenarios in urban India.

23

REFERENCES:

Brockerhoff, Martin, 2000: An Urbanizing World in Achieving Urban Food and Nutrition

Security in the Developing World, Focus 3 Brief 2 of 10, August 2000.

Engle, Patrice L, 2000: Urban Women: Balancing Work and Childcare in Achieving Urban

Food and Nutrition Security in the Developing World, Focus 3 Brief 8 of 10, August

2000.

International Food Policy Research Institute (IFPRI), 1998: Urban Challenges to Food and

Nutrition Security: A Review of Food Security, Health, and Caregiving in the Cities,

FCND Discussion Paper No. 51.

MSSRF and WFP, 2002: Food Insecurity Atlas of Urban India, Chennai, TTK Health Care

Limited.

National Family Health Survey-3, 2005-06: International Institute for Population Sciences,

Mumbai, India.

National Sample Survey Organization (NSSO), 2006: 61st Round, Report No. 508, Levels and

Patterns of Consumer Expenditure, 2004-05.

National Sample Survey Organization (NSSO), 2007: 61st Round, Report No. 509,

Households Consumptions of Various Goods and Services in India, 2004-05

National Sample Survey Organization (NSSO), 2007: 61st Round, Report No. 510, Public

Distribution System and Other Sources of Household Consumption in India, 2004-05,

Volume-1.


Employment and Unemployment Situation in India, 2004-05 (Part-1)


Participation of Women in Specified Activities alongwith Domestic Duties, 2004-05.

Sample Registration System, 2004: Baseline Survey Report-2004, Office of the Registrar

General, India.

Sample Registration System, 2007: Statistical Report 2006, Report No 4 of 2007, Office of

the Registrar General, India.

World Food Program (WFP), 2002: Urban Food Insecurity: Strategies for WFP, Policy

Issues, Agenda Item 5.

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