PABNA UNIVERSITY OF SCIENCE AND TECHNOLOGY
Department of Statistics
Faculty of Science
Course Title: Statistical Field Survey
Course Code: STAT-4110
Field Survey Report on
“The livelihood of rootless people in Pabna City”
A Survey Report Submitted in Partial Fulfillment of the Requirements for the
Degree of Bachelor of Science in Statistics
Submitted by:
i.
Redwan Islam (201602)
ii.
Md Rafiur Rahman (201620)
iii.
Anika Tabassum Raka (201627)
iv.
Md.Bayezid Molla (201611)
v.
Md.Hasibul Hossain Anto (201633)
vi.
Joytirtha Roy (201607)
vii.
Suharto Mollik (181630)
Supervised by:
Dr. Md. Shamim Reza
Professor
Department of Statistics
Pabna University of Science and Technology
DECLARATION
Here, we declare that this survey is an original work submitted by the following group members
who have all activity made a contribution. This survey has not been submitted for any degree
or examination at any other university. It does not contain any other person’s data, pictures,
graphs or other information, unless specifically acknowledged as being sourced from those
persons. Any other work of similar nature has been appropriately referenced in this survey.
1.Signed:
Date:
Redwan Islam
2.Signed:
Date:
Md.Bayezid Molla
3.Signed:
Date:
Md Rafiur Rahman
4.Signed:
Date:
Anika Tabassum Raka
5.Signed:
Date:
Md.Hasibul Hossain Anto
6.Signed:
Date:
Joytirtha Roy
7.Signed:
Date:
Suharto Mollik
2
APPROVAL CERTIFICATE
This is hereby to certify that the research students bearing Examination Roll No 201602,
201620, 201627, 201611, 201633, 201607 and 181630 of session 2019-2020, Department Of
Statistics, Faculty of Science, Pabna University of Science and Technology, Pabna. We
completed the report entitled "The livelihood of rootless people in Pabna city" in partial
fulfillment of the requirement for the degree of Bachelor of Science (Honor’s in Statistics on
11th January 2025). It is suitable for submission as a 4th year survey report, and no part of this
work has been submitted for any other degree or other purposes.
____________________________
Dr. Md. Shamim Reza
Professor
Department of Statistics
Faculty of science
Pabna University of Science and Technology, Bangladesh
3
Acknowledgement
First and foremost, all praise and gratitude are due to Almighty Allah for granting us the
strength, patience, and perseverance to complete this work successfully.
We would like to extend our heartfelt appreciation to our respected teachers, Dr. Md. Shamim
Reza, Professor, Department of Statistics, Pabna University of Science and Technology, for their
continuous guidance, valuable insights, and thoughtful suggestions throughout this study. His
encouragement and constructive feedback greatly enriched the quality of our research.
We extend our cordial thanks to Dr. Sabba Ruhi and Mira Khatun, the Department of Statistics
of Pabna University of Science and Technology teachers, for providing various facilities and
encouragement during work. We also wish to express our sincere thanks to all the participants
who took part in this survey and contributed their time and opinions. Their cooperation was vital
to the successful completion of this work.
Finally, we are deeply grateful to our parents and friends for their unwavering love, moral
support, and encouragement during every stage of this project. Their constant inspiration has
been our greatest strength. We are also grateful to all the other people who supported our field
survey.
4
ABSTRACT
Homelessness in Bangladesh reflects deep structural inequities that force thousands into
instability and social exclusion. This study investigates the socio-economic conditions and
livelihood challenges of rootless people in Pabna City, where poverty, unemployment,
riverbank erosion, and family disintegration remain critical drivers of displacement. Using a
descriptive cross-sectional survey, primary data from 219 respondents were collected through
purposive and snowball sampling. A structured questionnaire captured demographic,
economic, and social variables, which were analyzed using descriptive statistics, chi-square
tests, correlation analysis, and a binary logistic regression model. Logistic regression was
applied to identify the determinants of loan accessibility, as financial dependency emerged as
a key vulnerability factor. Results show that 96% of respondents are landless, 54% are in debt,
and most earn below 5000 BDT per month. Education and access to basic services remain
limited, although child vaccination and schooling rates are comparatively high. The findings
highlight that economic deprivation, lack of stable employment, and social negligence are the
principal causes of rootlessness. Policy interventions emphasizing income generation,
microcredit access, and community-based rehabilitation are crucial to restoring stability,
dignity, and social inclusion among the rootless population.
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Table of Contents
Chapter 1: Preliminaries
1.1 Introduction……………………………………...…………………………………….10
1.2 Statement of the Problem…………………...…………………………………………10
1.3 Objectives of the Study…………………...……………………………………...........11
1.4 Significance of the Study…………………...…………………………………..……..11
1.5 Research Questions…………………...…………………………………….................12
1.6 Location…………………...……………………………………..................................12
1.7 Scope of the Study and Limitations…………………...………………………..……..13
Chapter 2: Literature Review
2.1 Introduction…………………...…………………………………………………..…..14
2.2 Socio-Economic Factors………………………………………………………….…..14
2.3 Access to Social Services………………………………………………………….....14
2.4 Bangladesh Context…………………………………………………………….…….14
2.5 Conclusion…………………………………………………………………………....15
2.6 Research Gap………………………………………………………………….……...15
Chapter 3: Research Methodology
3.1 Introduction……………………………………………………………………..…..16
3.2 Research Design…………………………………………………………………….16
3.3 Study Area…………………………………………………………………………..16
3.4 Target Population…………………………………………………………………...16
3.5 Sampling Technique and Sample Size……………………………………………...17
3.6 Data Collection Instrument and Procedure…………………………………………17
3.7 Data Analysis……………………………………………………………………….18
3.8 Ethical Considerations……………………………………………………………...18
3.9 Limitations………………………………………………………………………….18
Chapter 4: Data Analysis and Presentation
4.1: Introduction……………………………………...…………………………………19
4.2: Frequency analysis
4.2.1 Age of respondents………………………………………………………….19
4.2.2 Gender of respondents………………………………………………………20
4.2.3 Family member count……………………………………………………….21
6
4.2.4 Grade studied……………………………………………………...…….…22
4.2.5 Type of Occupation……………………………………………………...…23
4.2.6 Average monthly income………………………………………………..…25
4.2.7 In debt……………………………………………………………...………26
4.2.8 Loan Source……………………………………………………………..…27
4.2.9 Land Ownership………………………………………………………....…28
4.2.10 Temporary residency……………………………………………….……...29
4.2.11 Residency loss issues………………………………………….………...…30
4.2.12 Seek help after rootless………………………………………………….…31
4.2.13 Government or others help……………………………………………..….32
4.2.14 Meals per day…………………………………………………………...…33
4.2.15 Protein consumption per week………………………………………….…34
4.2.16 Treatment medium……………………………………………………...…35
4.2.17 Child access to education…………………………………………...….….36
4.2.18 Child education medium…………………………………………….….…37
4.2.19 Child vaccination……………………………………………………….…38
4.2.20 National ID……………………………………………………….…….…39
4.2.21 Social negligence……………………………………………………….…40
4.3: Bivariate Analysis
4.3.1 Relationship between occupation status and debt………………………..…42
4.3.2 Relationship between occupation status and gender……………………..…43
4.3.3 Relevance between meals per day and protein consumption…………….…44
4.4: Statistical Analysis and Findings
4.4.1 Association between occupation type and salary range……………….……45
4.4.2 Association between grade studied and average monthly…………..………47
4.4.3 Association between loan amount impact meal consumption………………48
4.4.4 Association between occupation type and loan amount…………….………49
Chapter 5: Model Fitting Analysis
5.1 Model Fitting Analysis………………………………………………………...……50
5.2 Binary Logistic Regression………………………………………….………………50
5.3 Results of the fitted model……………………………………………..……………50
Chapter 6: Conclusion and Recommendation………………………..………54
7
List of Figure
Figures No. and Names
Page No
Figure 4.2.1: Histogram of Age of the respondents
20
Figure 4.2.2: Pie chart of Gender of the respondents
Figure 4.2.3: Bar plot of family member count
Figure 4.2.4: Bar plot of grade studied
Figure 4.2.5: Bar plot of occupation type
Figure 4.2.6: Bar plot of income groups
21
22
23
24
25
Figure 4.2.7: Pie chart of debt
Figure 4.2.8: Bar diagram of loan source
Figure 4.2.9: Bar diagram of Land Ownership
Figure 4.2.10: Bar diagram for Temporary residency
Figure 4.2.11: Bar diagram for residency loss issues
Figure 4.2.12: Pie chart of percentage seek help
Figure 4.2.13: Pie chart of percentage received help
Figure 4.2.14: Bar diagram of meals per day
26
27
28
29
31
32
33
34
Figure 4.2.15: Bar diagram for protein consumption
35
Figure 4.2.16: Bar diagram of treatment medium
36
Figure 4.2.17: Bar diagram of Child access to education
37
Figure 4.2.18: Pie chart for education medium
Figure 4.2.19: Bar diagram of child vaccination
Figure 4.2.20: Bar diagram for national ID
38
39
40
Figure 4.2.21: Bar diagram for social negligence
Figure 4.2.22: Crosstab figure of occupation status vs in debt
Figure 4.2.23: Crosstab figure of occupation status vs gender
41
42
43
Figure 4.2.24: Crosstab figure of meals per day vs protein
consumption
44
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List of Table
Table No. and Name
Table-4.1: Distribution of Age
Table-4.2: Frequency distribution of Gender
Table-4.3: Frequency distribution of family member count
Table-4.4: Frequency distribution of Grade studied
Table-4.5: Frequency distribution of Occupation
Table-4.6: Frequency distribution of income
Table-4.7: Frequency distribution of debt
Table-4.8: Frequency distribution of Loan source
Table-4.9: Frequency distribution of Land Ownership
Table-4.10: Frequency distribution of Temporary residency
Table-4.11: Frequency distribution of Residency loss issues
Table-4.12: Frequency distribution of Seek help after rootless
Table-4.13: Frequency distribution of Government or others help
Table-4.14: Frequency distribution of Meals per day
Table-4.15: Frequency distribution of Protein consumption per week
Table-4.16: Frequency distribution of Treatment medium
Table-4.17: Frequency distribution of Child access to education
Table-4.18: Frequency distribution of Child education medium
Table-4.19: Frequency distribution of Child vaccination
Table-4.20: Frequency distribution of National ID
Table-4.21: Frequency distribution of social negligence
Table-4.22: Cross tabulation between occupation status and debt
Table-4.23: Cross tabulation between occupation status and gender
Table-4.24: Cross tabulation between meals per day and protein
consumption
Table-4.25: Chi-Square tabulation between occupation type and
salary range
Table-4.26: Chi-Square tabulation between grade studied and
average monthly income
Table-4.27: Correlation tabulation between loan amount impact
meal consumption
Table-4.28: Chi-Square tabulation between occupation type and
loan amount
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CHAPTER ONE
PRELIMINARIES
1.1 Introduction
In an increasingly globalized and conflict-ridden world, the phenomenon of "rootlessness" has
become a pressing social, political, and humanitarian issue. Rootless people in individuals or
groups who lack a stable connection to a homeland, community, or cultural identity that are
found across various contexts, from refugees and stateless individuals to migrants, displaced
persons, and even those alienated within their own societies. Whether caused by war, forced
migration, political persecution, economic hardship, or cultural disintegration, rootlessness
often leads to profound psychological, social, and existential challenges. These individuals
frequently struggle with identity crises, marginalization, legal invisibility, and limited access
to basic human rights such as education, healthcare, and employment. This survey paper aims
to explore the multifaceted dimensions of rootlessness by examining its causes, categories, and
consequences. It also investigates how different societies and governments respond to the
needs of rootless populations, highlighting both effective and problematic approaches. By
surveying literature across health issue, sociology, anthropology, international law, and
political science, this paper seeks to provide a comprehensive overview of the current
understanding of rootlessness. Ultimately, the goal is to deepen awareness of this growing
issue and to inform more humane and inclusive policies that address the plight of rootless
people worldwide.
1.2 Statement of the Problem
Homelessness remains a persistent and complex socio-economic issue that reflects structural
inequalities within society. Despite rapid urbanization and economic progress, a significant
segment of the population continues to live without adequate housing, facing daily struggles
for survival. Homeless individuals often experience multiple dimensions of deprivation that
lack of access to shelter, healthcare, education, employment opportunities, and social security.
In many developing contexts, including Bangladesh, homelessness is not merely a personal
misfortune but a manifestation of broader systemic failures such as poverty, unemployment,
family disintegration, and insufficient social welfare policies. Yet, comprehensive empirical
data on the everyday lives, challenges, and coping strategies of homeless people remain
limited.
This study seeks to investigate the socio-economic conditions, primary causes, and human
rights concerns associated with homelessness. By conducting a field-based survey, the research
10
aims to generate insights that can contribute to the development of informed policies and social
interventions targeted at improving the living conditions and dignity of homeless individuals.
1.3 Objectives of the Study
The primary objective of this study is to explore and analyze the socio-economic conditions
and lived experiences of homeless individuals with an emphasis on understanding the
structural and personal factors contributing to homelessness. To achieve this overarching goal,
the study sets out the following specific objectives:
 To examine the socio-economic background of homeless individuals, including their
income sources, employment status, and access to basic opportunity.
 To identify the causes of homelessness, focusing on economic, social, and familial
dimensions that influence displacement.
 To assess the extent to which homeless individuals have access to basic human rights,
such as shelter, healthcare, food security, and education.
 To understand the challenges faced in daily life, including health risks, social problem
and safety concerns.
 To explore coping mechanisms and survival strategies adopted by homeless people in
urban and rural contexts.
To provide evidence-based insights and recommendations for policymakers, social workers,
and non-governmental organizations to formulate effective interventions aimed at reducing
homelessness and improving the quality of life for homeless populations.
1.4 Significance of the Study
This study on the lifestyle of homeless people provides critical insights into their socioeconomic conditions, causes of homelessness, and access to basic rights. It highlights the
challenges faced by one of the most vulnerable groups and identifies gaps in support systems.
The findings can inform policymakers and NGOs in designing targeted interventions, enhance
public awareness and advocacy and contribute to academic research on urban poverty and
social inequality. By understanding the root causes and daily struggles of homelessness, the
study supports preventive measures and strategies to improve the well-being and inclusion of
homeless individuals.
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The findings of this study are important for several reasons:
 Policy and Program Development: The insights can guide government and
non-governmental organizations in creating effective programs and interventions to
support homeless populations, ensuring better access to food, shelter, healthcare, and
education.
 Awareness and Advocacy: By documenting the lived experiences of homeless
individuals, the study raises social awareness, fostering empathy and encouraging
community involvement in addressing homelessness.
1.5 Research Questions







What are the socio-economic profiles of homeless individuals in terms of age, gender,
education, and occupation?
What are the main causes contributing to homelessness and how do these factors vary
across individuals?
How long have been experiencing homelessness and what factors influence the duration
of their condition?
To what extent do homeless individuals have access to essential rights including food,
shelter, safe drinking water, healthcare, and education?
What coping strategies and support systems are utilized by homeless individuals to
manage their daily needs?
How aware are homeless individuals of governmental and non-governmental programs
intended to support them?
What are the most pressing needs and challenges that affect the well-being and quality of
life of homeless individuals?
1.6 Location
This study was conducted in Pabna covering [districts] to ensure a representative sample of
rootless people.
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1.7 Scope of the Study and Limitations
 Scope of the Study:
This study focuses on examining the lifestyle of homeless individuals, emphasizing their socioeconomic conditions, primary causes of homelessness, and access to basic rights such as food,
shelter, healthcare, and education. It explores demographic characteristics, coping strategies,
and awareness of government and non-government support programs.
The research is geographically limited to Pabna District, providing an in-depth understanding
of homelessness within this context. Both quantitative and qualitative data are collected to offer
a comprehensive perspective on the daily experiences and challenges faced by homeless
populations. While the study does not aim to generalize findings to all regions, it provides
valuable insights to inform policy, social interventions, and further research on
urban homelessness.
 Limitations of the Study:
While this research offers valuable insights, several limitations must be noted.
Methodologically, the reliance on non-probability sampling (snowball and purposive)
enhances access to a hidden population but limits the statistical representativeness of the
sample, potentially skewing results towards more socially connected individuals. The crosssectional design captures a snapshot of rootlessness but cannot establish causality or trace its
development over time.
Conceptually, the study's dependence on self-reported data introduces the potential for biases,
including social desirability and subjective interpretation of the core concept of "rootlessness."
Furthermore, the focus on Pabna District, while specific, constrains the direct generalizability
of the findings to other regions with different socio-environmental dynamics.
Finally, practical constraints of time and resources limited the sample size and depth of
qualitative investigation. Despite these limitations, the study provides a crucial foundation for
understanding the nuanced experience of rootlessness and highlights the need for broader,
longitudinal research in the future.
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CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
Homelessness is a pervasive social issue that reflects the intersection of poverty,
unemployment, family disruption, and inadequate social safety nets. Scholars have defined
homelessness as the condition of individuals lacking a fixed, regular, and adequate nighttime
residence, often leading to severe deprivation in health, education, and social participation
(UN-Habitat, 2020). Various studies across developing countries, including Bangladesh,
indicate that homelessness is not merely a lack of shelter but a manifestation of
multidimensional poverty.
2.2 Socio-Economic Factors
Socio-economic factors play a crucial role in shaping the living conditions of homeless people.
Research shows that most homeless individuals come from low-income families, experience
unstable employment, and face challenges in accessing health care and education (Tipple &
Speak, 2009). The lack of permanent shelter leads to insecurity, poor nutrition, and exposure
to violence and disease. Many studies have also highlighted that natural disasters, family
disputes, addiction, and indebtedness are significant causes of homelessness in South Asia.
2.3 Access to Social Services
Access to social services and government support remains a persistent challenge. Despite
various policy frameworks aimed at poverty alleviation and social protection, many homeless
individuals remain excluded due to lack of identification documents and bureaucratic barriers
(Islam & Hossain, 2018). Women and children are particularly vulnerable, often exposed to
abuse, malnutrition, and limited educational opportunities.
2.4 Bangladesh Context
In Bangladesh, urban migration and rapid urbanization have worsened the housing crisis.
Studies by BRAC and UNDP (2019) reveal that homeless populations in Dhaka and other
major cities often depend on informal work, irregular income, and community-based support
for survival. However, non-governmental organizations (NGOs) and social workers have been
instrumental in providing temporary shelter, healthcare, and vocational training to help
reintegrate homeless people into society.
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2.5 Conclusion
The literature suggests that homelessness is both a cause and consequence of socio-economic
marginalization. Effective policy responses must therefore address structural inequalities,
create employment opportunities, ensure access to basic services, and strengthen communitybased rehabilitation programs. Understanding these dimensions through survey data can help
design evidence-based interventions to improve the well-being of rootless and homeless
populations.
2.6 Research Gap
Despite extensive research on homelessness, existing studies predominantly emphasize
structural causes, policy frameworks, or specific vulnerable groups often in developed Pabna
district contexts. There is a notable lack of empirical studies that investigate the daily lifestyles,
coping mechanisms, and lived experiences of homeless individuals, particularly in urban areas
of developing countries. Furthermore, while socio-economic conditions and access to basic
rights have been studied separately, few studies examine the inter play between demographic
factors, primary causes of homelessness, and accessibility of essential services. Additionally,
awareness and utilization of government and non-government support programs remain
insufficiently documented. Addressing these gaps, the present study seeks to provide a
comprehensive understanding of the socio-economic conditions, causes, and access to basic
rights of homeless populations, offering evidence-based insights for policy, social
interventions, and future research.
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CHAPTER THREE
RESEARCH METHODOLOGY
3.1 Introduction
This chapter outlines the methodological framework employed to investigate the socioeconomic and psychological conditions of rootless people in Pabna District. It details the
research design, study area, population, sampling techniques, data collection instruments,
procedures, and ethical considerations.
3.2 Research Design
A descriptive cross-sectional survey design was adopted for this study. This design was
appropriate as it facilitates the systematic collection of data from a sample of the population at
a single point in time to describe the characteristics and correlates of rootlessness.
A mixed-methods approach was utilized, integrating both quantitative and qualitative data
collection. This allowed for the quantification of key variables while also capturing the rich,
narratives and lived experiences of the rootless population.
3.3 Study Area
The study was conducted in Pabna District, located in north-western Bangladesh. Specific
upazilas (sub-districts) such as Pabna Sadar, Bagchipara, Akdonto, Chor, Ashutoshpur were
purposively selected due to their high vulnerability to riverbank erosion (Padma and Jamuna
rivers), significant rates of out-migration, and the presence of both char (river island) and urban
populations, which are critical for capturing diverse experiences of rootlessness.
3.4 Target Population
The target population for this study was defined as people who exhibit characteristics of
rootlessness, operationalized as:
 Individuals displaced at least once due to river erosion.
 Landless agricultural laborers with no ownership of homestead land.
 Long-term migrants who have returned to Pabna.
 Residents of unstable char areas.
 Individuals expressing a strong sense of disconnection from their community or place.
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3.5 Sampling Technique and Sample Size
Sampling Technique: Given the absence of a definitive sampling frame for the "rootless"
population, a multi-stage non-probability sampling technique was employed.
 Purposive Sampling was used to select the study Pabna Sadar and upazilas known for
erosion and migration.
 Snowball Sampling was then used to identify and recruit participants through referrals
from initial contacts, as this is effective for reaching hidden or hard-to-reach
populations.
Sample Size:
The area in Pabna district is covered by the survey. All of the rootless people in Bangladesh
consider as population. Here sampling units are the rootless people in Pabna.
𝑧 2 𝑝(1 − 𝑝)
𝑛=
𝐸2
Z = z-value (1.96 for 95%confidence level)
p= estimated proportion (0.5 for maximum variability)
E = margin of error (0.0662 or 6.62%)
A total of 219 participants were surveyed. Data collection continued until thematic saturation
was reached for the qualitative component.
3.6 Data Collection Instrument and Procedure
Socio-Demographic Profile: Age, gender, education, occupation, land ownership,
migration history, number of displacements.
Qualitative Section: Comprised open-ended questions exploring the meaning of "home,"
experiences of displacement, challenges, coping strategies, and aspirations.
Livelihood and Assets: Questions on income sources, debt, and access to services.
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Procedure: Data was collected over a one-month period. Trained enumerators conducted
face-to-face interviews in Bengali (the local language), each lasting approximately 15-20
minutes. Informed consent was obtained verbally before each interview.
3.7 Data Analysis
 Quantitative Data: Data from the closed-ended questions were coded, entered into
Microsoft Excel, and analyzed using SPSS (Version 26). Descriptive statistics
(frequencies, percentages, means, standard deviations) were used to summarize the data.
 Qualitative Data: Responses to open-ended questions were transcribed and translated into
English. Thematic Analysis was employed to identify, analyze, and report patterns
(themes) within the data through a process of coding and theme development.
3.8 Ethical Considerations
Ethical principles were strictly observed. Informed consent was obtained from all participants,
emphasizing voluntary participation and the right to withdraw at any time. Confidentiality and
anonymity were maintained, with personal identifiers excluded and data securely stored.
Interviews were conducted with empathy and cultural sensitivity to avoid distress. The study
adhered to principles of beneficence, aiming to provide insights for policy and social
interventions to improve the well-being of homeless populations.
3.9 Limitations
The use of non-probability sampling limits statistical generalizability, and reliance on selfreported data introduces potential biases. The cross-sectional design captures only a snapshot
of homelessness, and the geographic focus on Pabna District limits applicability to other
regions. Despite these constraints, the study offers a foundational understanding of the
lifestyle, challenges, and needs of rootless populations in the district.
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CHAPTER FOUR
Data Analysis and Presentation
4.1 Introduction
In this chapter, results of the questionnaires surveyed respondents’ data will be analyzed. In
order to know the nature and characteristics of the data, frequency distribution and graphical
representation could very useful. We have used different graphical methods for presenting
frequency of my data. Lastly this chapter is concluded with a summary on the hypothesis
findings.
4.2 Frequency Analysis
At first, we would like present frequency distribution and relevant graphs to have a quick
look of the data.
4.2.1 Age:
Table-4.1: Distribution of Age
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Figure 4.2.1: Histogram of Age of the respondents
Comment: The average age of the sampled individuals are about 43. The distribution of age
shows most of the respondent consists of the age group between 20 to 40 and very few are of
age greater than 80.
4.2.2 Gender:
Table-4.2: Frequency distribution of Gender
20
Figure 4.2.2: Pie chart of Gender of the respondents
Comment: The participants consist of 60% of male and 40% of female.
4.2.3 Family member count:
Table-4.3: Frequency distribution of family member count
21
Figure 4.2.3: Bar plot of family member count
Comment: Among the surveyed people we have found most of the families consist of 4
member which is about 30% and then family of 2 members which is about 23%. Only 5% of
the families consist of 6 members.
4.2.4 Grade studied:
Table-4.4: Frequency distribution of Grade studied
22
Figure 4.2.4: Bar plot of grade studied
Comment: About 57% of the respondents have no educational background and only 15% of
the respondents have studied up to grade 5. Very few have reported to study in higher grades.
4.2.5 Type of Occupation:
Table-4.5: Frequency distribution of Occupation
23
Figure 4.2.5: Bar plot of occupation type
Comment: In analysis of working professionals we have observed 36% of the respondents are
unemployed. Most of the working people are involved in Labor jobs which is about 13%, in
Brickyard with 8.7%,shopkeeper and farmer about 5%.
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4.2.6 Average monthly income:
Table-4.6: Frequency distribution of income
Figure 4.2.6: Bar plot of income groups
Comment: The average monthly income of the most of the individuals are under 5000.Only
7% of the respondents reported to have monthly income above 15000.
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4.2.7 In debt:
Table-4.7: Frequency distribution of debt
Figure 4.2.7: Pie chart of debt
Comment: Among the respondents 54% have reported to be in debt and 46% have no debt.
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4.2.8 Loan Source:
Table-4.8: Frequency distribution of Loan source
Figure 4.2.8: Bar diagram of loan source
Comment: About 44% of the people did not reveal their loan sources. Among the NGOs
BRAC has provided most of the loans followed by ASA and TAF.
27
4.2.9 Land Ownership :
Table-4.9: Frequency distribution of Land Ownership
Figure 4.2.9: Bar diagram of Land Ownership
Comment: 96% of the respondents reported they do not own any land and only 3% have
reported to have their own land.
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4.2.10 Temporary residency :
Table-4.10: Frequency distribution of Temporary residency
Figure 4.2.10: Bar diagram for Temporary residency
Comment: Most of the people have been living in temporary residency for 5 years.
29
4.2.11 Residency loss issues :
Table-4.11: Frequency distribution of Residency loss issues
Residency loss issues
Percentage
Debt
8.22%
Family Issue
28.77%
Health Issue
6.39%
Loan
0.46%
Loss In Business After Buying
Vehicle
0.46%
Natural Disaster
9.13%
Never Had A Permanent House
44.29%
Temporary
0.91%
Work Issue
1.37%
30
Figure 4.2.11: Bar diagram for residency loss issues
Comment: The analysis on residency loss issues show that 44% of the people never had a
permanent residency.28% lost their residency due to family issues, 9% due to natural disaster
and 8% due to debt.
4.2.12 Seek help after rootless :
Table-4.12: Frequency distribution of Seek help after rootless
31
Figure 4.2.12: Pie chart of percentage seek help
Comment:53% of the respondents stated that they seek help after being rootless.
4.2.13 Government or others help :
Table-4.13: Frequency distribution of Government or others help
32
Figure 4.2.13: Pie chart of percentage received help
Comment: 56% of the respondents said to have receive help from government and other
NGOs.
4.2.14 Meals per day:
Table-4.14: Frequency distribution of Meals per day
33
Figure 4.2.14: Bar diagram of meals per day
Comment: About 75% of the respondents reported to have meals 3 times a day and 25%
reported to have 2 meals per day.
4.2.15 Protein consumption per week:
Table-4.15: Frequency distribution of Protein consumption per week
34
Figure 4.2.15: Bar diagram for protein consumption
Comment: Most of the people consuming protein 2 to 3 times per week. Only 2% have
reported that they consume protein almost everyday.
4.2.16 Treatment medium:
Table-4.16: Frequency distribution of Treatment medium
Treatment medium
Percentage Treatment taken from
Government hospital
84.76%
Homeopathy treatment
0.48%
Non-government and government hospital
6.19%
Non-Government hospital
3.33%
Village doctor
5.24%
35
Figure 4.2.16: Bar diagram of treatment medium
Comment: About 85% of the respondents stated that they receive treatment from government
hospital and very few about 1% seek homeopathy treatment.
4.2.17 Child access to education:
Table-4.17: Frequency distribution of Child access to education
36
Figure 4.2.17: Bar diagram of Child access to education
Comment: The people are aware of their child education.82% of the respondents said they
send their child to school.
4.2.18 Child education medium:
Table-4.18: Frequency distribution of Child education medium
37
Figure 4.2.18: Pie chart for education medium
Comment: The children are mostly getting their education from Government school. Only
7% from Madrasha and Non-Government school and very few from BRAC.
4.2.19 Child vaccination:
Table-4.19: Frequency distribution of Child vaccination
Row Labels
Count of Child vaccination ensured
Yes
100.00%
(blank)
0.00%
38
Figure 4.2.19: Bar diagram of child vaccination
Comment: All children are ensured vaccination.
4.2.20 National ID:
Table-4.20: Frequency distribution of National ID
Row Labels
Have National ID
No
5.48%
Yes
94.52%
39
Figure 4.2.20: Bar diagram for national ID
Comment: 95% of the people have their national id.
4.2.21 Social negligence:
Table-4.21: Frequency distribution of social negligence
Row Labels
Social Negligence
No
75.34%
Yes
24.66%
40
Figure 4.2.21: Bar diagram for social negligence
Comment: 75% of the respondents reported to experience social negligence.
41
4.3 Bivariate Analysis
In bivariate analysis we observe the relationship between two variables.
4.3.1 Relationship between occupation status and debt
Table-4.22: Cross tabulation between occupation status and debt
Figure 4.2.22: Crosstab figure of occupation status vs in debt
Comment: The persons who have jobs are more in debt than the unemployed or it can be said
that the employed persons are provided more loans.
42
4.3.2 Relationship between occupation status and gender
Table-4.23: Cross tabulation between occupation status and gender
Figure 4.2.23: Crosstab figure of occupation status vs gender
Comment: In occupation status we see male have more presence then female. Men are more
actively involved in jobs than women.
43
4.3.3 Relevance between meals per day and protein consumption
Table-4.24: Cross tabulation between meals per day and protein consumption
Figure 4.2.24: Crosstab figure of meals per day vs protein consumption
Comment: Those who have meal 3 times a day are more likely to consume protein per week
but mostly 2 times per week.
44
4.4 Statistical Analysis and Findings
A chi square test is a statistical test commonly used for testing independence and goodness of
fit. Testing independence determines whether two or more observations across two populations
are dependent on each other. In both cases the equation to calculate the chi square statistic is,
𝑛
(𝑂𝑖 − 𝐸𝑖 )2
𝑥 =∑
𝐸𝑖
2
𝑖=1
𝑊ℎ𝑒𝑟𝑒,
𝑂𝑖 = 𝑡ℎ𝑒 𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦
𝐸𝑖 = 𝑡ℎ𝑒 𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦
n=𝑡ℎ𝑒 𝑛𝑜. 𝑜𝑓 𝑐𝑒𝑙𝑙𝑠
4.4.1 Association between occupation type and salary range
Table-4.25: Chi-Square tabulation between occupation type and salary range
𝐻0 : There is no association
𝐻1 : Association exists
Comment: Asymptotic significance shows the observed p value is less than 1% level of
significance which means we can reject the null hypothesis and the test is significant.
So the conclusion is salary range is significantly different for different occupation types.
45
We observe those involved in Labor, shopkeeper, brickyard, painter, farmer are more in higher
salary range compared to others.
46
4.4.2 Association between grade studied and average monthly income
Table-4.26: Chi-Square tabulation between grade studied and average monthly
income
𝐻0 : There is no association
𝐻1 : Association exists
Grade studied
0
1
2
3
4
5
6
7
8
9
Female
21.46%
0.00%
2.28%
1.37%
3.65%
5.48%
2.74%
1.83%
0.46%
0.46%
Male
36.07%
0.91%
4.57%
1.83%
1.37%
9.59%
0.00%
1.83%
3.65%
0.46%
47
Comment: From the chi square test we see that observed p value less than the level of
significance of 1%. It means we reject the null hypothesis and there is a significant association
between grade studied and average monthly income category.
The analysis of grade studied to income group shows that people who have studied up to 5th
grade are more likely to be in higher income groups. But the analysis also shows that people
with higher than 5th grade study are less in high income groups. It is because we see less
individuals have studied more than 5th grade so the proportion of their working status is less.
We can also see that people with no educational background are more in numbers in high
income groups. This phenomena can be explained by the fact that the jobs they are involved in
does not require any educational qualification rather it requires people with more experience.
So because of experience of work people are earning more than the people in education.
4.4.3 Association between loan amount impact meal consumption
Table-4.27: Correlation tabulation between loan amount impact meal
consumption
Comment: There is a positive correlation between loan amount and meals per day. It means
people are affected in their livelihood because of loans.
48
4.4.4 Association between occupation type and loan amount
Table-4.28: Chi-Square tabulation between occupation type and loan amount
Comment: The chi square test between occupation type and loan source shows a significant
association which means different amount of loan are provided to different professionals.
49
CHAPTER FIVE
Model Fitting Analysis
5.1 Model Fitting Analysis:
Model Fitting describes the relationship between a response variable and one or more predictor
variables. There are many different models that one can fit including simple linear regression,
multiple linear regression, logistic regression (binary logistic regression, nominal logistic
regression, ordinal logistic regression) and so on. In this survey, binary logistic regression is
used. There are many situations when we would like to predict an outcome that is Ordinal (for
instance Strongly Disagree to Strongly Agree). In such situation, we can use Ordinal Logistic
Regression to assess the impact of one of more predictor variables on the outcomes. Binary
Logistic regression analysis is a method to determine the reason-result relationship of
independent variable(s) with dependent variable.
5.2 Binary Logistic Regression:
Binary logistic regression is used in this survey to model the relationship between a binary
dependent variable and one or more independent variables (e.g., screen time duration, device
usage, and parental monitoring). This statistical technique predicts the probability of an
outcome (e.g., "Yes" for affected vision) based on the predictors and provides insights into
their significance and strength of association. Odds ratios (Exp(B)) help interpret the effect of
each independent variable on the likelihood of vision problems, while Nagelkerke R² assesses
the model's explanatory power.
5.3 Results of the fitted model
50
Comment: The Nagelkerke R Square value is 0.424 means that approximately 42% of the
variation in the dependent variable can be explained by the independent variables in the logistic
regression model.
51
52
Summary of hypothesis:
Hypothesis:
𝐻0 : There is no significant association between dependent variable and independent
variables.
Alternative Hypothesis
DF
P-value
Decision
𝐻1 : There is a significant association
between age and having loan
1
<0.01
𝐻0 accepted
𝐻1 : There is a significant association
between gender and having loan
1
.881
𝐻1 rejected
𝐻1 : There is a significant association
between occupation time and having loan
19
.815
𝐻1 rejected
𝐻1 : There is a significant association
between average monthly income and
having loan
1
.487
𝐻1 rejected
Comment: Age has a significant impact on loan access. The odds ratio of age is .951
indicating for each year increase in age people are less likely to receive loan. It means
younger adults are more likely to receive loans.
53
CHAPTER SIX
Conclusions and Recommendations
Conclusion
The present field survey titled “The Livelihood of Rootless People in Pabna City” provides an
in-depth understanding of the socio-economic conditions and daily struggles of homeless
individuals living in the Pabna district. The findings reveal that most of the respondents are
landless and live in temporary shelters without stable income or job security. Poverty,
unemployment, family conflicts, and natural disasters were identified as the main causes
behind their rootlessness. More than half of the respondents are in debt, mostly through NGO
microloans, while government assistance remains limited.
Recommendation
 Government Support and Policy
The government should create long-term rehabilitation programs, including housing schemes,
skill training, and employment opportunities for rootless people.
 Access to Education and Health
Free primary education and healthcare facilities should be made available through mobile or
community-based services.
 Social Awareness
Awareness campaigns should be organized to reduce social stigma and discrimination against
rootless individuals.
 NGO and Community Involvement
NGOs and local communities should collaborate to provide food, shelter, counseling, and
vocational training.
 Data Collection and Monitoring
A national database should be created to identify rootless populations and track their progress
over time.
 Psychological Support
Counseling and mental health support programs should be developed, especially for children
and women living without shelter
 Public–Private Partnership
Encourage private sectors and businesses to support social housing and employment initiatives
for the rootless.
54
References
1. BRAC & UNDP. (2019). Urban poverty and homelessness in Bangladesh: A situational
analysis. Dhaka, Bangladesh: BRAC Research and Evaluation Division.
2. Islam, M. S., & Hossain, M. A. (2018). Homelessness and access to social services in
Bangladesh: A policy perspective. Bangladesh Development Studies, 41(2), 87–104.
3. Tipple, G., & Speak, S. (2009). The hidden millions: Homelessness in developing
countries. Routledge.
4. UN-Habitat. (2020). World cities report 2020: The value of sustainable urbanization.
Nairobi: United Nations Human Settlements Programme.
5. World Bank. (2021). Poverty and equity brief: Bangladesh. Washington, DC: World Bank
Group.
6. Rahman, M. M., & Akter, S. (2022). Socio-economic factors influencing urban
homelessness in Bangladesh. Journal of Social Science and Humanities Research, 8(4),
55–68.
55
Survey Questionnaire on the Lifestyle of Rootless People
1) What is your age?
_______
2) What is your gender?
☐ Male ☐ Female ☐ Other
3) What is your marital status?
☐ Married ☐ Unmarried ☐ Other
4) How many members are there in your family?
_______
5) What is your highest level of education completed?
_______
6) Are you currently employed?
☐ Yes ☐ No
If yes, what kind of work do you do?
_______
7) What is your average monthly income?
☐ Below 5,000 BDT ☐ 5,000–10,000 BDT ☐ 10,000–15,000 BDT ☐ Above 15,000 BDT
8) Do you currently have any loans?
_______
9) From where did you take the loan and what is the amount?
_______
10) Where did you previously live (district/area)? Did you own any land or property there?
_______
11) How long have you been living without a permanent home?
_______
12) What do you think is the main reason for losing your home?
☐ Job loss ☐ Family conflict ☐ Natural disaster ☐ Addiction ☐ Health issue ☐ Debt
☐ Other (please specify): _______
56
13) Have you received help from anyone after becoming homeless?
☐ Yes ☐ No
14) Have you received any government or non-governmental assistance?
☐ Yes ☐ No
If yes, what kind of benefit did you receive?
_______
15) How many times do you eat per day?
_______
16) Do you have access to safe drinking water?
☐ Yes ☐ No
17) How much do you spend on food per week (rice, meat, etc.)?
_______
18) When you get sick, where do you seek treatment?
_______
19) Do your children have access to education?
☐ Yes ☐ No
If yes, where or through which institution?
_______
20) Are you and your family able to eat three meals a day regularly?
☐ Yes ☐ No
21) Do you have a National ID card?
☐ Yes ☐ No
22) Do you feel socially excluded?
☐ Yes ☐ No
Thanks for cooperation
That’s all for now
57