Socio-economic status of transferred and non-transferred urban slums: a case study from Faisalabad.
Ahmed, Riaz ; Mustafa, Usman ; Khan, Atta Ullah 等
The rapid urbanisation in last four decades has been the key
problem of almost all the developing countries of the world. The
population pressure on the cities resulted in the emergence of urban
slums. Poverty, illiteracy, unemployment, poor health facilities,
sanitation and non-availability of clean drinking water, etc. are the
common characteristics of slum-dwellers. A lot of work has been done on
slums both in Pakistan and at international level, but very little
research work has been made in the context of transferred and
non-transferred urban slums, especially in Faisalabad, which is the
third most populous city of Pakistan. In this research paper an attempt
has been made to find the socio-economic conditions of people residing
in urban slums of Faisalabad. It was found that most of the slum
population was facing worst socio economic conditions. The research is
based on primary data which was collected through a field survey on a
questionnaire. The universe of the study is inhabitants of 104 slums of
Faisalabad. The sample slums have been selected on the basis of
variation in dwelling units by applying stratified random sampling
technique and proportion allocation method. To explore the
socio-economic conditions of slums, different techniques such as cross
tabulation, independent sample T-test and quantification of different
qualitative variables have been applied. A comparison between socio
economic conditions of transferred and non-transferred slums has also
been made. It has been found that socio-economic conditions of large
slums are better than those of small and transferred slums are better
than those of non-transferred.
JEL Classification: O15, R11, R23, R31, Q18, D10
Keywords: Migration, Development, Human Development, Urban
Planning, Rehabilitation, Socio-economic Status, Urban Slums, Faisalabad
1. INTRODUTCTION
The rapid urbanisation has become a burning challenge across the
developing countries of the world for the last four decades. The
population pressure on the cities has caused many problems like
environmental pollution, sanitation, education, health, traffic level
and housing etc. In this context, housing is one of the most important
issues related to urbanisation. Slums are reflected as the carbuncle in
cities and looked extemporaneously and arbitrarily [Shafqaat, et al.
(2013). The share of world urban population was 32 percent in 1950, it
rose up to 39 percent in 1980 and 48 percent in 2000, which reflects
that 3 out of 10 people were living in cities in 1950. In 2011, about
half of the world population was living in the big cities and at the end
of the third decade of this century; that make up the formation as 6 out
of 10 people [World Bank (1999)]. Pakistan's town populace is fixed
to become identical to its rural population in the year 2030. This needs
for an effective urban planning instrument to confirm universal
distribution of simple municipal amenities, regulator of the spread of
slums, reducing of effluence and the control of crime and political
might [Khan, et al. (2012)].
"The earth has urbanised even faster than originally predicted
by the Club of Rome in its notoriously Malthusian 1972 report, Limits of
Growth. In 1950 there were 86 cities in the world with a population over
one million; today there are 400, and by 2015, there will be at least
550. Cities, indeed, have absorbed nearly two-thirds of the global
population explosion since 1950 and are currently growing by a million
babies and migrants each week. The present urban population (3.2
billion) is larger than the total population of the world in 1960. The
global countryside, meanwhile, has reached its maximum population (3.2
billion) and will begin to shrink after 2020. As a result, cities will
account for all future world population growth, which is expected to
peak at about 10 billion in 2050" [Davis (2004)]. Cities indeed
have observed nearly two-third of the global population explosion and
are currently growing by a million babies and migrants each week across
the world [UN Population Division (2002)], whereas, the situation is
even more dangerous in the developing countries. Alike rest of the
developing countries, the share of urban population was 17.8 percent in
1951 which rose to 28.3 percent in 1981 and 32.5 percent during 1998 in
Pakistan [Population Census Organisation (2001)]. Such higher
urbanisation trends arise mainly because of inadequate employments
avenues and low quality of life. People belonging to low income group
are unable to build appropriate shelter for themselves in the big
cities. Resultantly, they are forced to establish squatter settlements
and these squatter settlements are called urban slums. Poverty,
illiteracy, unemployment, poor health facilities, poor sanitation and
non-availability of clean drinking water facilities are the common
characteristics of the inhabitants of urban slums.
The concept of "Slums" was firstly defined in Vaux's
1812 (vocabulary of the English language) where it is synonymous with
'racket' or 'criminal trade'. According to
Encyclopedia of Britannica, Slum is defined as "a residential area
that is physically and socially deteriorated and where satisfactory
family life is impossible. Thus, bad housing is major index of slum
conditions which includes bad dwellings, improperly heated rooms,
absence of family privacy and no space for recreational facilities
[Britannica (2010)].
The root cause of emergence of urban slums is poverty as poor
cannot afford to have a reasonable house to live and they settle
themselves in open spaces of city, which leads to the emergence of urban
slums. Slums show the worst of urban poverty and inequality [Mustafa
(2007)]. The other major cause is the rapidly increasing population.
Growing number of people rush to the slums of the city create urban
crises [Akhtar (2009)]. Most of the migrants coming from rural areas are
poor, and hence the urban areas remain numerically dominated by the
poor. The migrants have originated largely from the economically
depressed areas of the country [Sarwar and Rahman (2004)].
Urban poor face serious problems due to population pressure,
deterioration in the physical environment and quality of life [Sribas
and Samita (2013)]. Housing conditions have deteriorated in urban
centers because of population explosion and rural urban migration
[Siddique (2007)]. People residing in the slums are poor. The worse
socioeconomic conditions do not allow them to live a healthy life. They
do not have access to sanitation. They are unable to get safe water
supply [Naveed and Anwar (2014)]. Unemployment rate is very high in such
areas [Ali (2010)]. Housing facilities in the planned schemes are too
expensive to be availed. Therefore low income government employees as
well as the laborers have no choice except urban slums for the
affordable accommodation [Qadeer (1983)].
Slums do not have proper drainage. The streets are narrow and
unpaved. Slums dwellers have to face water stagnation in rainy season.
This makes the environment of that area very unhygienic. Such
environment causes a number of diseases [Daziuban, et al. (2006)]. Urban
Slums are characterised by poor living conditions, inadequate, social
services coupled with high level of diseases [Agyaro-odure (2009);
Baloch and Mustafa (2012)]. There is need to take steps to improve the
physical condition of dwelling places like basic amenities of toilets,
proper drainage, sewerage system and water supply [Sufaira (2013)].
The poor slum dwellers face many problems including health at top.
Women are unable to get proper treatment during pregnancy. So mortality
rate is very high in such areas [Awashti and Agarwal (2003)]. Slums
improvement programs should be started in Pakistan through local
councils [Hina (1999)]. There are both transferred and nontransferred
slums in Pakistan. The socio-economic conditions of transferred slums
are better than those of non-transferred [Bhatti (2001)].
The study in hand is a pioneering effort to make comparison of
socio-economic conditions of inhabitants of non-transferred slums and
those of transferred slums in Faisalabad. To materialise the primal
objectives of the research, the study firstly, explores the
socio-economic profile of Katchi Abadis' inhabitants on the basis
of specific set of indicators i.e. health, community participation,
educational attainment, income level, demographic features, employment
status, housing status and sewerage system. Secondly, it examines the
socio-economic conditions of slums of Faisalabad. Thirdly, the study in
hand investigates the difference in socio-economic conditions of
different kind of slums and also suggests some policy recommendations to
curb out the problem of slum dwellers and its spread in Faisalabad.
2. METHODOLOGY
2.1. Sampling
The following section briefly discusses the target population of
Faisalabad, sampling frame and technique. Furthermore, selection of
sample urban units and respondent is also presented, followed by data
analysis tools and techniques adopted in the study.
2.1.1. Target Population
Total number of slums in Faisalabad are 106, while the information
available regarding dwelling units is 104, thus, the universe consisted
of 104 Katchi Abadis (slums) of Faisalabad.
2.1.2. Sampling Frame
A list of 104 Katchi Abadis of Faisalabad was received from the
Directorate of Katchi Abadis, Government of the Punjab. This list was
used as a sampling frame.
2.1.3.Sampling Technique
In order to take the representative sample, stratified random
sampling technique was adopted. From the list of Katchi Abadis it was
found that number of dwelling units varied from 42 to 2851. It was
assured that the Katchi Abadis differ on following basis:
* Educational facilities available within the area.
* Involvement of NGO's.
* Area of the Katchi Abadi.
* Medical facilities available.
Majority of the Katchi Abadis (33) have number of dwelling units
below 80, followed by 32, covered in the stratum of 81-200 units. There
were only five numbers of Katchi Abadis which come in the stratum where
there dwelling units number were above 1000.
2.1.4. Selection of Sample Urban Slums
The samples of Katchi Abadis were selected on the basis of
variability of dwelling units in different Katchi Abadis. Following
proportional allocation method was used [Parel, et al. (1973)
n = N x [summation]
[N.sub.h][S.sup.2.sub.h]/[[N.sup.2][d.sup.2]/[Z.sup.2]] +
[summation][N.sub.h][S.sup.2.sub.h]
Where:
N = Total number of Katchi Abadis (104).
[N.sub.h] = Total numbers of Katchi Abadis in "h"
Stratum.
d = (Sampling error acceptable for study). Due to resource and time
constraint 0.1 error was accepted at Abadis level.
Z = Confidence level = 95 percent.
n [congruent to] 15
(For detail see Appendix A-1).
Proportional allocation method was used to obtain Sample from each
stratum:
[n.sub.i] = [N.sub.h] / N x n
(For detail see Appendix A-2).
Almost all selected slums are located near road, small and medium
enterprises factory areas. Most of the slums are generally build in
low-lying, unhygienic, and environmentally poor areas. These are the
rejected areas where there is no civic facilities available/ Even no
electricity because these are mostly government abandon land, initially
inhabitant settled there in tents and kacha houses and latterly after
giving bribes to local municipal administrative authorities make their
houses pacca (concretes. The local political parties and influence
people also support than. In some cases even they encourage the
immigrants to settle down. Latterly, they registered their vote in local
area and also use than to grasp government land. Shafqaat (2013) also
revealed that transportation positions, zones which are already settled
and small scale and cottage manufacturing play an important part in the
formation of slums in Faisalabad.
2.1.5. Selection of Sample Respondents
After Selection of Sample Katchi Abadis, the sample size of
respondents was found. This was done on the basis of variability in
Income. For this purpose a pre-survey was conducted from 36 households
in six strata. Proportional allocation method was adopted to determine
the sample size of the respondent which was 213. (For detail see
Appendix A-3).
This over all sample size was proportionally distributed in
different strata (For detail see Appendix A-4).
2.2. Data Analysis
Quantification of different qualitative variables, Cross
tabulation, methods of vital statistics, percentiles and test of
significance (Independent sample T-test) statistical tools were used for
data analysis.
3. ANALYSIS OF DATA AND INTERPRETATION OF RESULTS
The summary of results of four variables (Education, Health, Income
and Housing) is given as follows:
3.1. Education
Education is one of the basic parameters to evaluate the
socio-economic conditions of people. To find the literacy rate generally
accepted definition of literacy rate was used. According to this
definition, a person who can read and write a single line of Urdu is
literate. The overall literacy rate is calculated 65.91 percent. Only
0.18 percent people hold master degrees or above. This shows that slums
dwellers have very low trend towards higher education. The literacy rate
is higher among males (70.04 percent) than those of females (60.93
percent). Literacy rate is found to be comparatively higher in the slums
which are notified, regularised and close to the city centre (Mai De
Jhugi, Partab Nagar, Fire Brigade, Malik Pura, Muslim High School, Tariq
Abad) and low in those which are not regularised and situated away from
the city centre (Bishan Singh Wala, Gharib Abad, Pull Tariq Abad, Girga
Ghar, Railway Phatak, Malkhanwala, old water works and Madan Pura) while
it is moderate in those which have been regularised and found at
moderate distance from the city center (Chowk Choudhry Floor mills,
Bahadar Singh Wala and Manawala sq. no.80). For detail see Appendix A-5.
3.1.2. Field of Education
The percentage of general Education, Engineering, Health, Law,
Agriculture, Commerce and Computer was calculated 92.23 percent, 0.62
percent, 0.99 percent, 0.00 percent, 0.49 percent, 2.22 percent and 0.62
percent respectively. This shows that people residing in slums have low
inclination towards higher and professional education.
3.1.3. Reason for not Attending the School
The major reason for not attending the school is poverty. In 93
percent of the cases, children are not going to school due to financial
reasons. So to increase the literacy rate, there is need of income
generation activities in such area.
3.2. Health Profile
Slums badly affect the health conditions of their dwellers due to
lack of health services, basic infrastructure, and poor sanitation and
environment condition [Yusuf (2007)]. In Manila and Philippines,
children living in slums were found to be nine times more victims of
tuberculosis (TB) than children living in other areas [Fry, et al.
(2002)]. Overcrowding in slums is the major cause of psychological
stress [Sundari (2003)]. Attack rate of ARI (Acute respiratory
infections) and ADD (Acute diarrheal diseases) was estimated 14.6
percent and 7.73 percent respectively in under 5 year children of
Gokaepari settlements of Delhi. These diseases were attributed to lack
of sanitation and lack of portable water for drinking [Gupta, et al.
(2007). Crude birth rate, infant mortality rate and incidence of
disability were used as parameters to find health profile in current
study.
3.2.1. Crude Birth
Crude birth rate indicates the number of live births occurring
during the year, per 1000 population estimated at midyear (1). This rate
is higher in poorer and non-transferred slums (51.02, 38.10, 36.36,34.48
and 32.89 in Old Water Works GM Abad, Fire Brigade K.A, Bishan Singh
Sala, Pull Tariq Abad Girga Ghar and Madan Pura respectively) while it
is lower in transferred and settled slums (18.69, 15.27 and 9.62 in
Chowk Choudary Floor Mills, Mai Di Jhugi and Pertab Nagar respectively)
than the national level (For detail see Appendix A-6).
3.2.2. Infant Mortality
Infant mortality is the number of infants dying before reaching one
year of age, per 1000 of live birth in a given year. The infant
mortality was calculated 111.11 which is much higher than national
level. (2) (For detail see Appendix A-7).
There are many other studies which show high infant mortality in
slum areas. Gupta and Pandey (2007) found that 97.0 percent of the
deliveries were conducted in institutions like nursing home and
hospitals etc., in case of new urban colonies of East Delhi, while it
was only 29.0 percent for the slum dwellers of same locality. Gupta, et
al. (2007) found that the level of care during the deliveries was very
low among the mothers of slums areas. About 68 percent of the deliveries
were carried out in the houses, without a skilled nurse, mid wife or
doctor in such areas as compared to 21 percent and 7 percent deliveries
in rural and urban areas respectively. Kimani, et al. (2007) reported
that prevalence of diarrheal diseases among the children of people
residing in slums of Nairobi was 32 percent while in rural areas it was
17 percent. Similarly, Gupta (2007) showed that in eastern Delhi, the
prevalence of diarrheal diseases (per 1000) were highest among children
of slum residents (25.1) and least among those residing in new urban
colonies (2.2). This difference was due to poor unhygienic living
conditions in the slums areas.
3.2.3. Incidence of Disability
Out of disabled people 45.45 percent were found to be crippled
which is dangerous. (For detail see Appendix A-8).
3.3. Income
Average household income is found in Partab Nagar (Rs 9822.5)
followed by Chowk Choudhry Floor Mills (Rs 9615), Fire Brigade (Rs
9500), Bahadar Singh Wala (Rs 9317.5), Muslim High School Tariq Abad (Rs
9285), Old water works G.M Abad (Rs 9035.5), Malkhanwala (Rs. 9037.5),
MadanP ura (9027.5), Gharib Abad (Rs 8702), Manawala Sq. no. 80 (Rs
8685), Malik Pura (Rs 8671.5), Railway Phatak no.8 (Rs 8667.5), Pull
Tariq Abad Girga Ghar (Rs 8565) and Bishan Singh Wala at the bottom with
income Rs. 7400 per household. Low average income shows that majority of
population is living below poverty line. (For detail see Appendix A-9).
3.4. Housing Status
The information related the housing conditions such as number of
rooms, wall and roof material and source of drinking water have been
covered under this aspect. Due to poverty, the slum dwellers could not
afford a proper piece of land and usually selected a neglected area or
vacant plots and developed slums there. Most of the slum dwellers were
found to have katcha houses, where wood was used as a supporting
material. In the similar manner, the houses of people residing in
Coimbatore area of Tamilnadu were made up of similar kind of material
with more than 43.4 percent people living in katcha houses [Sundari
(2003)].
3.4.1. Number of Rooms
Is an important parameter to measure the socio-economic conditions
of inhabitants of slum-dwellers. More than 23 percent of the households
from selected slums are living in a single room dwelling unit followed
by 42.25 percent in two rooms, 18.78 percent in three rooms. (For detail
see Appendix A-10).
Similar to this study, the single and two room accommodation was
very common among the slum dwellers of Coimbatore of Tamilnadu [Sundari
(2003)] and Aligarh city of Uttar Pradesh [Rahman (2008)]. In another
study conducted by Ray (2002) in Calcutta, it was found that about 96
percent of slum dwellers had single room accommodation.
3.4.2. Wall and Roof Material
About 87 percent of the walls have been constructed with the help
of baked bricks while 13 percent with unbaked bricks. Similarly, it has
also been calculated that majority of roofs have been constructed by
cement and iron sheets but significance use of wood/bamboo (36.60
percent) reflects that socio-economic conditions of the slum-dwellers
are worse. (For detail see Appendix A-11).
3.4.3. Source of Drinking Water
The drinking water of Faisalabad is not clean. It was estimated
that about 65.75 percent of the slum-dwellers are using the water from
motor pumps. That is why; hepatitis is very common in these slums. These
results are consistent with WHO (2008), which narrates that poor water
quality is one of the basic causes of morbidly and mortality worldwide.
Growing number of poor people who lack basic needs, such as access to
clean water are more victims to the diseases driven by malnourishment
and air, water and soil pollutants [Pimentel (2007)]. The slums dwellers
of Nairobi city use sewerage water, rain water and water from broken
pipes for various purposes such as drinking and washing etc. [Amuyunzu
and Taffa (2004)]. Afsar (1999) found that urban slums dwellers in
Bangladesh were deprived of water supply to their homes and the average
time to collect the water from a common stand pipe or well was 30minutes
per trip and at least two trips were needed to collect the bucket of
drinking water. Further Osamanu (2007) found that most of the urban poor
of Tmale city of Ghana collected water from the sources located in
distance. In another study, the water supply to the 128 migrants in
Tirupur slums was found to be of poor quality and unfit for human
consumption [Sundari (2003)]. In similar way, the quality of drinking
water was found substandard in the slums of Tamilnadu [Sundari 2003) and
Delhi, Karswara, et al. (2005)].
3.5. Hypothesis
Whether socio-economic conditions of inhabitants of non-transferred
slums are different than those of transferred slums.
3.5.1. Housing Status
The p-value of housing status is P=0.014 which is less than
[varies] = 5 percent = 0.05 (level of significance). This shows there is
significance difference between housing status of transferred and
non-transferred slums. Mean reflects that housing status of transferred
slum is better than that of non-transferred slum.
3.5.2. Education Attainment
The P-value of education attainment is P = 0.776 which is greater
than [varies] = 5 percent = 0.05 (level of significance). This shows,
there is no significance difference between the educational attainment
of the two slums.
3.5.3. Household Income
P = 0.003 < [varies] = 5 percent = 0.05 (level of significance)
which shows there is significance difference between the household
income of transferred and non-transferred slums. Mean reflects that
household income of transferred slum is better than nontransferred slum.
4. CONCLUSION AND RECOMMENDATION
4.1. Conclusion
The rapid urbanisation during last four decades has given birth to
urban slums. The poor slum dwellers face worse socio-economic
conditions. The streets are unpaved and there is poor system of
sanitation and drainage. Although, literacy rate was found reasonable
yet the trend towards higher education is almost equal to nothing. The
reason behind it is when the children grow in age; they are forced to do
physical work as source of earning. There is high birth and infant
mortality rate. The housing status is poor. Most of the people live in a
single room house. Majority of the houses have no separate kitchens and
toilets. About half of the slum population lives in unpaved houses. A
large number of the population is deprived of clean drinking water which
has given birth to infectious 'diseases. The majority of slum
residents has very low income and is living below the poverty line. It
was found that property rights of some slums have been transferred to
the people residing there. These are called transferred urban slums
while still there are some slums whose property rights have not been
transferred to dwellers living there. These are called non-transferred
slums. The socio-economic conditions in transferred slums were found
better than those in non-transferred.
4.2. Recommendations
(i) Urban planning should be focused to cater the increasing
pressure of urbanisation. Steps should be taken to improve the physical
conditions of slums. The basic infrastructure should be upgraded.
(ii) Government should take steps to provide basic health
facilities and clean drinking water. High infant and maternal death can
be substantially reduce by providing basic sanitation facilities in
these areas.
(iii) The property rights should be given to those whom these
rights have not been given so far but steps should be taken to stop the
emergence of new slums.
(iv) Government should lay stress on women development. A strategy
should be made for establishing the proper marketing network for the
sale of good produced by them.
(v) Keeping in view Oringi Pilot Project model, community
participation based development programs should be launched to improve
the physical conditions of these poor areas.
(vi) NGO's should play their role to improve the
socio-economic conditions of these most deprived areas in cities.
APPENDIX
Table A-1
Selection of Sample Katchi Abadi on the Basic Of Variation in Number
of Household
Stratum Mean S.D [S.sup.2.sub.h][N.sub.h] [N.sub.h]
1 58.75758 14.01122 0.056862 33
2 131.0625 31.88076 0.05917 32
3 276.6875 39.0405 0.019882 16
4 427.3636 42.34447 0.009817 11
5 725.4286 132.0151 0.033123 7
6 1857.4 812.2831 0.191257 5
Stratum [N.sub.h] x [S.sup.2.sub.h]
1 1.876456
2 1.893435
3 0.318114
4 0.107992
5 0.231858
6 0.926255
5.35411
Table A-2
Selected Katchi Abadis
Sr. No. Selected Katchi Abadis No of Dwelling Units
1 Bishan Singh Wala 42
2 Chowk Choudhry Floor mills 56
3 Muslim High School, Tariq Abad 58
4 Gharib Abad 66
5 Madan Pura 279/R.B 78
6 Bahadar Singh Wala 97
7 Malik Pura 133
8 Old Water Works 116
9 Manawala Sq. 80 180
10 Malkhanwala 256
11 Railway Phatak No. 8 288
12 Pull Tariq Abad, Girga Ghar 408
13 Fire Brigade 443
14 Partab Nagar 638
15 Mai Di Jhugi (Bilal Gunj) 2851
Source: Researcher's own calculations.
Table A-3
Selection of Sample Size on the Basis of Variation per Capita Income
Stratum Mean S.D [S.sup.2.sub.h][N.sub.h]
1 1810 809.1971 0.199872
2 1433.333 615.042 0.181726
3 1556.333 581.0393 0.139382
4 2126.667 772.1118 0.131814
5 1299.767 285.6644 0.048348
6 1320 319.9375 0.058747
Total
Stratum [N.sub.h] [N.sub.h] x [S.sup.2.sub.h]
1 2135 426.7267
2 3703 671.8205
3 4648 647.8475
4 5957 785.216
5 4466 215.9222
6 19957 1166.888
Total 3914
36 Households were interviewed in 6 strata to estimate the variation
in socio-economic condition of households.
Table A-4
Selection of Sample Respondents
Sr. No. Name of Selected Katchi Abadi Distribution of Sample
1 Bishan Singh Wala 10
2 Chowk Choudhry floor mill 13
3 Muslim High school Tariq Abad 14
4 Gharib Abad 15
5 Madan Pura 18
6 Bahadar Sing Wala 11
7 Old Water works 13
8 Malik Pura 14
9 Manawala Sq.80 19
10 Malkhanwala 13
11 Railway Phatak No. 8 15
12 Pull Tariq Abad Girga Ghar 13
13 Fire brigade 15
14 Partab Nagar 14
15 Mai Di Jhugi 14
Source: Researcher's own calculations.
Table A-5
Literacy Rate
Literacy Literacy
Literacy Rate Rate
Stratum Colony Rate (Male) (Female)
1. Bishan Singh Wala 23.26% 36.84% 12.50%
Chowk Choudhry Floor Mills 65.91% 73.47% 56.41%
Muslim High School, Tariq 81.33% 89.19% 73.68%
Abad
Gharib Abad 48.05% 48.89% 46.88%
Madan Pura 50.77% 46.48% 55.93%
Sub Total 56.17% 59.28% 52.60%
2. Bahadar Singh Wala 77.05% 81.82% 71.43%
Old Water Works (GM Abad) 51.43% 52.94% 50.00%
Malik Pura 82.93% 89.80% 72.73%
Mananwala Sq. No. 80 69.72% 76.92% 59.09%
Sub Total 70.50% 76.80% 62.41%
3. Malkhana Wala 59.42% 59.52% 59.26%
Railway Phatak No. 8 46.43% 52.17% 39.47%
Sub Total 52.29% 55.68% 47.69%
4. Pull Tariq Abad Girga Ghar 54.17% 63.41% 41.94%
Fire Brigade K.A 88.37% 86.67% 90.24%
Sub Total 72.78% 75.58% 69.44%
5. Partab Nagar 80.95% 90.24% 72.09%
6. Mai Di Jhugi (Bilal Gung) 88.89% 90.74% 86.67%
Overall Literacy Rate 65.91% 70.04% 60.93%
Source: Researcher's own calculations.
Table A-6
Crude Birth Rate
Less Than Total
Colony One Year Population CBR/1000
Bishan Singh Wala 2 55 36.36
Chowk Choudhry Floor Mills 2 107 18.69
Muslim High School, Tariq Abad 2 94 21.28
Gharib Abad 2 94 21.28
Madan Pura 5 152 32.89
Sub Total 13 502 25.90
Bahadar Singh Wala 0 92 0.00
Old Water Works (GM Abad) 5 98 51.02
Malik Pura 3 111 27.03
Mananwala Sq. No. 80 4 131 30.53
Sub Total 12 432 27.78
MalkhanaWala 0 89 0.00
Railway Phatak No. 8 4 140 28.57
Sub Total 4 229 17.47
Pull Tariq Abad Girga Ghar 3 87 34.48
Fire Brigade K.A 4 105 38.10
Sub Total 7 192 36.46
Partab Nagar 1 104 9.62
Mai Di Jhugi (Bilal Gung) 2 131 15.27
Total 39 1590 24.53
Source: Researcher's own calculations.
Table A-7
Infant Mortality Rate
Less Than Birth in Infant
One Year No. of Last 12 Mortality
Particulars Children Infant Months Rate /1000
Male 26 3 29 103.44
Female 22 3 25 120
Total 48 6 54 111.11
Source: Researcher's own calculations.
Table A-8
Incidence of Disability
Particulars Male Female Total % of Total Disables
Blindness 0 1 1 9.09%
Deaf/Mute 0 0 0 0.00%
Crippled 3 2 5 45.45%
Madness 1 0 1 9.09%
Mentally Retarded 2 0 2 18.18%
More Than 1 Disability 1 0 1 9.09%
Other 1 0 1 9.09%
Total 8 3 11 100.00%
Source: Researcher's own calculations.
Table A-9
Average Income of Household
Stratum Colony Average Income
1 Bishan Singh Wala 7400
Chowk Choudhry Floor Mills 9615
Muslim High School, Tariq Abad 9285
Gharib Abad 8702
MadanPura 9027.5
2 Bahadar Singh Wala 9317.5
Old Water Works (GM Abad) 9037.5
Malik Pura 8671.5
Mananwala Sq. No. 80 8685
3 MalkhanaWala 9037.5
Railway Phatak No. 8 8667.5
4 Pull Tariq Abad Girga Ghar 8565
Fire Brigade K.A 9500
5 Partab Nagar 9822.5
6 Mai Di Jhugi (Bilal Gung) 9500
Overall Average 9220
Source: Researcher's own calculations.
Table A-10
Number of Rooms
Stratum Colony One Two Three
1. Bishan Singh Wala 7 2 0
ChowkChoudhry Floor Mills 0 11 2
Muslim High School 2 3 5
Gharib Abad 6 7 1
MadanPura 6 8 1
Sub Total 21 31 9
2. Bahadar Singh Wala 1 4 4
Old Water 2 7 3
Malik Pura 3 6 2
Mananwala Sq. No. 80 8 8 1
Sub Total 14 25 10
3. MalkhanaWala 3 6 2
Railway Phatak No. 8 2 7 3
Sub Total 5 13 5
4. Pull Tariq Abad 6 6 1
Fire Brigade K.A 0 5 7
Sub Total 6 11 8
5. Partab Nagar 0 8 2
6. Mai Di Jhugi 4 2 6
G. Total 50 90 40
% of G. Total 23.47% 42.25% 18.78%
Stratum Colony Four Five Six > Six
1. Bishan Singh Wala 1 0 0 0
ChowkChoudhry Floor Mills 0 0 0 0
Muslim High School 4 0 0 0
Gharib Abad 1 0 0
MadanPura 2 1 0 0
Sub Total 7 2 0 0
2. Bahadar Singh Wala 0 0 0 2
Old Water 1 0 0 0
Malik Pura 3 0 0 0
Mananwala Sq. No. 80 2 0 0 0
Sub Total 6 0 0 2
3. MalkhanaWala 2 0 0 0
Railway Phatak No. 8 0 2 1 0
Sub Total 2 2 1 0
4. Pull Tariq Abad 1 0 0 0
Fire Brigade K.A 2 1 0 0
Sub Total 3 1 0 0
5. Partab Nagar 3 1 0 0
6. Mai Di Jhugi 1 2 0 0
G. Total 22 8 1 2
% of G. Total 10.33% 3.76% 0.47% 0.94%
Source: Researcher's own calculations.
Table A-11
Wall and Roof Material
% of Total % of Total
Sample Sample
Wall Material Houses Roof Material Houses
Baked Bricks 86.90% Lantern (RCC/RBC) 10.80%
Unbaked Bricks 13.10% Cement / Iron Sheet 48.40%
Wood/Bamboo 0 Wood/Bamboo 36.60%
Other 0 Other 4.20%
Source: Researcher's own calculations.
REFERENCES
Afsar, R. (1999) Rural-Urban Dichotomy and Convergence: Emerging
Realities in Bangladesh. Environment and Urbanisation 2, 235-243.
Agyarko-oduro, F. (2009) Slum Upgrading and Prevention--the Time to
Act is Now in Urbanisation and Decentralisation. Retrieved, February
2015 at http://www. modernghana.com/news/244339/l/slum-upgrading-and-prevention-the-time-to-act-isn.html.
Akhtar, T. (2009) Migration and Living Condition in Urban Slums:
Implications Food Security. Unnayan Onneshan, The Innovators, Centre for
Research and Action on Development, Dhaka, Bangladesh.
Ali, K. R. E. (2010) Life in Slums: A Case Study of Bahawalpur.
Afro Asian Journal of Anthropology and Social Policy 11, 31-50.
Amuyunzu, M. and N. Taffa (2004) The Triad of Poverty:
Environmental and Child Health in Nairobi Informal Settlements. Journal
of Health and Population in Developing Countries 6, 1-14.
Awasthi, S. and S. Agarwal (2003) Determinants of Childhood
Mortality and Morbidity in Urban Slums in India. Indian Pediatrics 40:1,
1145-1160.
Baloch, Shamasud din and U. Mustafa (2012) Human Settlement in
Pakistan: A Survey on Urban Sprawl in Islamabad. LAP Lambert Academic
Publishing, Germany. ISBN13: 978-3-8484-2300-2, paperback, 140 Pages
LAMBERT Academic Publication. Germany.
https://www.lap-publishing.com/catalog/details//store/gb/book/978-3-84842300-2/human-settlements-in-
pakistan:a-survey-on-urban-sprawl-of-islamabad,
http://www.amazon.eom/Usman-Mustafa/e/B00J8DRJWM
Bhatti, S. A. (2001) Socio-economic Conditions of Katchi
Abadis' Inhabitants and Impact of Katchi Abadi on Vicinity
Residents: A Case Study of Lahore. Department of Economics. Lahore: GC
University Lahore.
Britannica, Encyclopedia (2010) Encyclopedia of Britannica.
Encyclopedia Britannica, Inc. Corporate Site.
Davis, Mike (2004) Planet of Slums: Urban Involution and the
Informal Proletariat. New Left Review 26, March-April 2004, pp. 5-34.
Dziuban, Eric J., Jennifer L. Liang, Gunther F. Craun, Vincent
Hill, Patricia A. Yu, John Painter, Matthew R. Moore, Rebecca L.
Calderon, Sharon L. Roy, and Michael J. Beach. Surveillance for
Waterborne Disease and Outbreaks Associated with Recreational
Water--United States, 2003-2004. MMWR Surveill Summ. December 22, 2006 /
55(SS 12); 1-24.
Fry, S., B. Cousins, and K. Olivola (2002) Health of Children
Living in Urban Slums in Asia and the Near East: Review of Existing
Literature and Data. Environmental Health.
Gupta, M., J. S. Thakur, and R. Kumar (2007) Reproductive and Child
Health Inequities in Chandigarh (UT) of India. Journal of Urban Health
85, 291-299.
Gupta, R. K. and A. Pandey (2007) Status of Children in Eastern
Delhi: Care During Delivery, Immunisation and Occurrence of some Acute
Diseases. Indian Journal of Community Medicine 32, 88-89.
Hina, I. (1999) Role of Government in the Improvement of Katchi
Abadis. Unpublishedthesis, Department of Economics, Govt. College,
Lahore.
Karswara, S. and V. Sangwan (2005) Popularisation of Water
Purifying Technology at Household Level in Slum Areas. Journal of Human
Ecology 18, 117-119.
Khan Sohaib, Amal Aslam, Maria Zubair, and Ali Rehan (2012)
Integrating Urban Datasets: The Path to Effective Socio-Economic
Planning in urban Pakistan. IGC Pakistan, Policy Brief February 2012.
Kimani, E., E. Zulu, and C. C. Undie (2007) Health and Livelihood
Implication of the Marginalisation of Slum Dwellers in the Provision Of
Water and Sanitation Services in Nairobi City. In Workshop on Urban
Population, Development and Environment Dynamics in Developing
Countries, Nairobi 11-13 June.
Mustafa, U. (2007) Solving the Urban Sprawl: A Case Study of Kot
Lakhpat, Lahore. In Nadeem Ul Haque and Durr-e-Nayab (eds.) Cities:
Engine of Growth. Islamabad: Pakistan Institute of Development
Economics.
Naveed, M. and M. Anwar, (2014) Socio-Economic Condition and Health
Status of Urban Slums: A Case Study of Jogo Chak, Sialkot. Asian Journal
of Social Sciences and Humanities 3:4.
Osumanu, I. K. (2007) Environmental Concerns of Poor Households in
Low Income Cities: The Case of Tmale Metropolis, Ghana. Geo Journal 68,
343-355.
Parel, C. P., et al. (1973) Sampling Design and Procedure. Social
Server Research Design, Quezons City Trial edition, p. 27.
Population Census Organisation (1998) Population and Housing Census
of Pakistan. Islamabad. Statistics, Division, p. 5.
Population Census Organisation (2001) Population and Housing Census
1998. Federal Bureau of Statistics, Islamabad, Pakistan.
Population Information Program (2002) Population Reports: Meeting
the Urban Challenge. 30:4.
Qadeer, M. A. (1983) Lahore: Urban Development in the Third World.
Vanguard Book Ltd, Lahore.
Rahman, A. (2008) Assessing Income-wise Household Environmental
Conditions and Disease Profile in Urban Areas: Study of an Indian City.
Geo Journal 65, 211-227.
Ray, S. (2002) Living Conditions and Health of Two Social Groups
Inhabiting a Squatter Settlement in Calcutta, India. International
Journal of Anthropology 17, p. 209.
Sarwar, Salima and R. Sadikur (2004) Urbanisation, Rural or Urban
Migration and the Street Children in Hazardous Condition: A Case Study
in Rajshahi City. Association for Community Development -ACD; Rajshahi.
Shafqaat M, Abdul Ghaffar, Ibtisam Butt, Muhammad Sajjad, and Nasir
Aslam (2013) Application of GIS in the Spatial Analysis of Slums in
Faisalabad, Pakistan. Sci .Int. (Lahore), 25:3,457-460.
Siddiqui, T. (2007) Cities Engines of Growth. Islamabad: Pakistan
Institute of Development Economics.
Sribas, Goswami and Manna Samita (2013) Urban Poor Living in Slums:
A Case Study of Raipur City in India. Global Journal of Human Social
Science Sociology and Culture 13:4 Version 1.0 Year 2013. Sidho Kanho
Birsha University, India.
Sufaira, C. (2013) Socio Economic Conditions of Urban Slum Dwellers
in Kannur Municipality. Journal Of Humanities And Social Science
(IOSR-JHSS) 10:5, 12-24.
Sundari, S. (2003) Quality of Life of Migrant Households in Urban
Slums. In Proceeding of Third International Conference on Environment
and Health, Chennai, India, 15-17 Nov.
UN Population Division (2002) World Urbanisation Prospects: The
2001 Revision Data Tables and Highlights. United Nations Population
Division, ESA/P/WP.173, New York, USA.
United Nations (1988) Karachi. Population Growth and Policies in
Megacities Series. New York, p. 19.
World Bank (1999) World Development Indicators 1999. Report
No.19140. The World Bank, Washington, D.C.
WHO (2008) Community-based Strategies for Breast Feeding Promotion
and Support in Developing Countries. Geneva.
Yusuf, S., K. Nabeshima, and W. Ha (2007) Income and Health in
Cites: The Messages from Stylised Facts. Journal of Human Health 84,
35-40.
Riaz Ahmed <
[email protected]> is PhD Scholar, Department
of Economics, Preston University, Islamabad Campus. Usman Mustafa
<
[email protected]> is Head, Department of Business Studies and
Chief Project Evaluation and Training Division, Pakistan Institute of
Development Economics, Islamabad. Atta Ullah Khan is Assistant
Professor, Department of Economics, Preston University, Islamabad
Campus.
(1) Crude birth (per 1000 people) in Pakistan was last measured at
27.28 in 2010 according to world development Indicators.
(2) infant mortality rate (per 1000 of live births) in Pakistan was
last measured at 69.70 in according to world development indicators.
Table 1
Category of Dwelling Units
Stratum No of Dwelling Units No. of K/A
1 Below 80 33
2 81-200 32
3 201-350 16
4 351-500 11
5 501-1000 7
6 Above 1000 5
Source: Researcher's own calculations.
Table 2
Group Statistics of Non-Transferred V/s Transferred Katchi Abadis
Group Statistics
P value
Std. when Equal
TNT N Mean Std. Error Variance
Deviation Mean Assumed
Housing Transferred 14 2.79 1.051 .281 .353
Status Not Transferred 19 1.84 .958 .220
Educational Transferred 14 3.21 2.359 .631 .072
Attainment Not Transferred 19 3.47 2.816 .646
Household Transferred 14 9822.5 .267 .071 .000
Income Not Transferred 19 8685 .513 .118
