Anuradhapura's food insecure areas
by Dr. Amara Satharasinghe, Deputy Director, Department of Census and
Statistics
Finding ways to reduce poverty and inequity is a daunting challenge
for local, national, and international decision-makers. One important
aspect of the challenge to reduce poverty and inequity is that poor
people tend to be clustered in specific places. Aggregated,
national-level poverty data mask this sub national variation. Poverty
maps can help uncover poor areas that might otherwise go undetected.
Poverty mapping, the spatial representation of poverty, is becoming
an increasingly important instrument to identify areas where development
lags and where investments, infrastructure and services could have the
greatest impact.
According to the official statistics, 23 per cent of the population
of Sri Lanka is poor. Therefore, eradication of poverty has been given a
high priority in the agenda of the Sri Lanka Government. Several
government and, local and international non-governmental organisations
are implementing various projects aiming at development and poverty
eradication.
Food insecurity is strongly linked with poverty. Food insecurity is
defined as the limited or uncertain availability of nutritionally
adequate and safe foods or limited or uncertain ability to acquire
acceptable foods in socially acceptable ways. Food insecurity is a
spatial phenomenon, and varies considerably across geographical areas.
A Divisional Secretary (DS) division is quite a large area and
therefore, there can be a wide variation in levels of food insecurity
within DS divisions. Therefore, for more efficient targeting it is
necessary to identify poor/food insecure areas at lower administrative
units so that level of food insecurity within such units can be
considered homogeneous.
Due to the lack of secondary data, preparation of poverty/food
insecurity maps at lower level administrative units is not possible.
The Department of Census and Statistics in collaboration with the
United Nations World Food Program, recently conducted a study to make an
attempt to explore the possibility of devising an alternative method to
obtain data required for classification of lower level administrative
units according to poverty/food insecurity. In this study, a Knowledge
Based Scoring method was adopted to obtain the necessary data required
for the classification at Grama Niladhari (GN) division level.
Grama Niladharis were trained and instructed to assign scores to a
set of indicators related to poverty/food insecurity based on their
experience and knowledge gained, by working long periods of time in
their respective areas (GN Division). In addition to these selected
indicators, some indicators at GN division level that have been
released, based on the data collected from the Census of Population and
Housing (2001) were also used in this study.
Altogether 22 indicators; 14 from KBS method, 8 from Census of
Population and Housing - 2001, capable of capturing variation in food
insecurity were used in this study. Statistically, these 22 indicators
were reduced to an index known as Vulnerability to Food Insecurity while
retaining most of the important characteristics of the original
indicators.
There are 694 GN divisions in the Anuradhapura district.
Statistically, these 694 GN divisions of the Anuradhapura district were
classified into 4 groups using the scores of this index.
The GN divisions falling into the first group were called most
vulnerable to food insecurity. GN divisions falling into 2nd, 3rd and
4th groups were labelled as more, less and least vulnerable to food
insecurity. For easy reference, this classification was displayed in a
map of GN divisions of the Anuradhapura district.
GN divisions classified as most vulnerable and more vulnerable were
shaded in red and orange colours respectively. Yellow and green were the
colours used to shade GN divisions falling into less and least
vulnerable to food insecurity. Field verifications and comparison of
classification against infrastructure facilities of GN divisions
indicated the high reliability of the findings of this study. This study
has been carried out for Badulla and Monaragala districts as well.
These maps can have a substantial impact on decision-making by
improving and validating geographic targeting of poor areas; making
resource allocation more accountable, transparent, and equitable;
igniting national and local-level debate and awareness on poverty;
encouraging broader participation; facilitating coordination between and
within institutions; and improving the credibility of institutions.
Monitoring is an important component of any project. The maps so
compiled can be used to monitor the impact of interventions implemented
within GN divisions. Repeating this study preferably at two-year
intervals and observing the shifts in levels of vulnerability of GN
divisions to poverty/food insecurity, impact of interventions could be
assessed. |