Baseline Population and Socioeconomic Census Slums of Dhaka (North and South) and Gazipur City Corporations, 2015-16

Urban Primary Health Care Services Delivery Project Local Government Division Ministry of Local Government, Rural Development & Cooperatives

Prepared by: International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) Government of the People’s Republic of Bangladesh Ministry of Local Government, Rural Development & Cooperatives Local Government Division Urban Primary Health Care Services Delivery Project

Baseline Population and Socioeconomic Census: Slums of Dhaka (North and South) and Gazipur City Corporations, 2015-16

Submitted by: International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b)

2 3 Contents Preface…………………………………………………………………………………………………………………………….8 Abbreviations…………………………………………….………………………………………………………….……….10 Summary of Key Findings and Implications………………….. ……………………………………….……….11 Chapter One ...... 12 Introduction ...... 12 1.1 Background of the Project...... 12 1.2 Objective of the Study...... 13 1.3 Organization of the Report...... 14 1.4 Funding Sources and Technical Support...... 14 Chapter Two ...... 15 Methods and Procedures ...... 15 2.1 Selection of Slums...... 15 2.2 Concepts and Definitions...... 15 2.3 Recruitment and Training of Field Workers ...... 18 2.4 Mapping and Household Listing...... 19 2.5 Questionnaires: Baseline Population and Socioeconomic Census ...... 19 2.6 Field Work- Baseline Population and Socioeconomic Census...... 20 2.7 Data Management ...... 20 2.8 Quality Control/Security...... 21 Chapter Three...... 22 Population Characteristics...... 22 3.1 Population Size...... 22 3.2 Age and Sex Characteristics...... 22 3.3 Dependency Ratio...... 23 3.4 Household Size and Type...... 24 3.5 Marital Status...... 25 Chapter Four...... 26 Living Condition...... 26 4.1 Ownership of Land and Dwelling...... 27 4.2 Housing Condition...... 28 4.3 Construction Material Used for Dwelling...... 29

4 4.4 Water and Sanitation ...... 31 4.5 Source of Light and Fuel for Cooking ...... 33 4.6 Garbage Disposal ...... 34 Chapter Five ...... 36 Socioeconomic Condition...... 36 5.1 Educational Qualification ...... 37 5.2 Occupation...... 39 5.3 Household Possessions...... 40 5.4 Household Expenditure and Saving ...... 41 Chapter Six ...... 45 Migration of Household Head...... 45 6.1 Duration of Migration ...... 45 6.2 Causes of Migration ...... 46 6.3 Origin of Migration...... 47 Chapter Seven ...... 48 Challenges to Establish HDSS in Slums ...... 48 7.1 Challenges...... 48 7.1.1 Selection of Slums ...... 48 7.1.2 Defining the Study Area...... 49 7.1.3 GIS Coordinate of House ...... 49 7.1.4 Numbering- Bari and Household ...... 50 7.1.5 Absentee Respondent - Locked House...... 50 7.1.6 Respondent Busy...... 51 7.1.7 Security of Field Worker/Tab...... 52 7.1.8 Problems Related to Migration...... 52 7.1.9 Threat to Abolish Slum ...... 52 7.2 Strategies to Overcome Challenge...... 53

Tables Table 3.1.1: Distribution of Households and Distribution of Population by Slum Locations ...... 23 Table 3.2.1: Distribution of Population by Five-Year Age groups and Sex...... 23

5 Table 3.2.2: Distribution of Population (per cent) by Broad Age Group and Slum Locations ...... 24 Table 3.3.1: Dependency Ratios by Slum Locations ...... 25 Table 3.4.1: Distribution of Households by Type and Sex of Household Heads...... 25 Table 3.5.1: Distribution of Population+ by Marital Status and Sex...... 26 Table 4.1.1: Distribution of Households (per cent) by Ownership of Land and Slum Location .. ……………………………………………………………………………………………………………………………………………28 Table 4.1.2: Distribution of Households (per cent) by Ownership of Dwelling and Slum Locations……………………………………………………………………………………………………………………...…….29 Table 4.2.1: Distribution of Households (per cent) by Number of Dwelling and Slum Locations ...... 29 Table 4.2.2: Distribution of Households (per cent) by Dwelling Area and Slum Locations..... 29 Table 4.3.1: Distribution of Households (per cent) by Construction Material of Roof and Slum Locations ...... 30 Table 4.3.2: Distribution of Households (per cent) by Construction Material of Wall and Slum Locations ...... 31 Table 4.3.3: Distribution of Households (per cent) by Construction Material of Floor and Slum Locations ...... 31 Table 4.4.1: Distribution of Households (per cent) by Source of Drinking Water and Slum Locations ...... 32 Table 4.4.2: Distribution of Households (per cent) by Those Sharing Water Source and Slum Locations ...... …………32 Table 4.4.3: Distribution of Households (per cent) by Type of Latrine and Slum Locations....33 Table 4.4.4: Distribution of Households (per cent) by Those Sharing Latrine and Slum Locations ...... 33 Table 4.5.1: Distribution of Households (per cent) by Source of Light and Slum Locations.. .34 Table 4.5.2: Distribution of Households (per cent) by Type of Fuel for Cooking and Slum Locations ...... 34 Table 4.5.3: Distribution Households (per cent) by those Sharing Cooking Place and Slum Locations ...... 34 Table 4.6.1: Distribution of Households (per cent) by Garbage Dumping System and Slum Locations ...... 35 Table 4.6.2: Distribution of Households (per cent) by Frequency of Garbage Collection and Slum Locations...... 36 Table 5.1.1: Distribution of Population+ by Years of Schooling and Sex ………………………………39 Table 5.1.2: Distribution of Children+ (per cent) by Type of School and Slum Locations………39 Table 5.2.1: Distribution of Population by Occupation+ and Sex ...... 41 Table 5.2.2: Distribution of Population (per cent) by Occupation+ and Slum Locations ...... 41 Table 5.3.1: Distribution of Households (per cent) Owning Selected Items by Slum Locations ...... ….42 Table 5.4.1: Distribution of Households (per cent) by Total Expenditure during Last Month ...... 43 Table 5.4.2: Distribution of Households (per cent) by Expenditure on Food during Last Month ...... 43 Table 5.4.3: Distribution of Households (per cent) by Expenditure on Health during Last Month ...... 43

6 Table 5.4.4: Distribution of Households (per cent) by Expenditure on Education during Last Month ...... 44 Table 5.4.5: Distribution of Households (per cent) by Amount Saved during Last Month..... 45 Table 6.1.1: Distribution of Migrants (per cent) by Duration of Migration+ and Slum Locations ...... 47 Table 6.2.1: Distribution of Migrants (per cent) by Cause of Migration+ and Slum Locations ...... 47 Table 6.3.1: Distribution of Migrants (per cent) by Origin of Migration+ and Slum Locations ...... 48

Figure Fig 1.1.1: Urban and Rural Population: Middle Income Countries and Bangladesh, 1950-2050 ...... 13 Fig 2.1.1: Location of Slums: Dhaka North, Dhaka South and Gazipur City Corporations ...... 17 Fig 5.1.1: Distribution of Children+ (per cent) by Type of School and Sex ...... 39 Fig 7.1.2.1: View of Korail Slum in Dhaka...... 50 Fig 7.1.3.1: Space in between Two Houses...... 49 Fig 7.1.4.1: Finding the House...... 50 Fig 7.1.5.1: Locked Household and Note for Availability ...... 51 Fig 7.1.6.1: Respondent Busy ...... 51 Fig 7.1.7.1: Security Issue...... 52

References References ...... 54

Appendix Appendix A: Key Findings- Baseline Population and Socioeconomic Census, 2015-16...... 55 Appendix B: Member of Technical Review Committee...... 58 Appendix C.1: Distribution of Slums by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014...... 59 Appendix C.2: Distribution of Households by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014...... 60 Appendix C.3: Distribution of Population by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014...... 60 Appendix D.1: Under-Five Care (per cent) when Mothers Work Outside...... 62 Appendix D.2: Loan Received (per cent) from NGO/Others ...... 62 Appendix D.3: NGO/Samity Membership...... 62 Appendix D.4: Members Affected by Violence, Robbery etc During the Last Six Months..... 63 Appendix E.1: Baseline Population and Socioeconomic Census, 2015-16 (All HH)...... 64 Appendix E.2: Baseline Socioeconomic Census, 2015-16 (Sample HH)...... 66

7 Preface

The baseline population and socioeconomic census 2015-16 was undertaken by icddr,b in the selected slums of Dhaka (North and South) and Gazipur City Corporations. The specific objective of the baseline census was to collect data on the demographic, socioeconomic and migration characteristics of the study population. The data of the baseline census will primarily be used to establish the Health and Demographic Surveillance System (HDSS) in these slums. The ultimate aim of the HDSS is to provide tools for monitoring and evaluating impacts of health services those are being provided by NGOs to urban poor with support from the Urban Primary Health Care Services Delivery Project under Local Government Division of Ministry of Local Government, Rural Development and Cooperatives.

Urban Primary Health Care Services Delivery is one of the largest projects in the South Asian Countries to deliver primary health care to the urban people with the partnership of Urban Local Bodies and NGOs. The project does not only deliver services, it also works to raise standard of the primary health care services in urban Bangladesh.

The draft report of the survey was reviewed by a Technical Review Committee consisted of experts from the government, non-governmental and international organizations as well as researchers and professionals working in different Universities/Institutions. I would like to extend my gratitude and appreciation to the members of the committee for their contributions at different phases of the project.

I express my thanks to icddr,b for its efforts in successful completion of the task that will lead to establish the HDSS.

December 29, 2016 (Md. Abu Bakr Siddique) Project Director (Joint Secretary) UPHCSDP, Local Govt. Division Ministry of LGRD&C

8 Abbreviations:

ADB Asian Development Bank ASA Association for Social Advancement BBS Bangladesh Bureau of Statistics brac Bangladesh Rural Advancement Committee Co-PI Co-Principal Investigator DSK Dushtha Shasthya Kendra DNCC Dhaka North City Corporation DSCC Dhaka South City Corporation GCC Gazipur City Corporation HDSS Health and Demographic Surveillance System icddr,b International Centre for Diarrhoeal Disease Research, Bangladesh INDEPTH The International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries NIPORT National Institute of Population Research and Training NGO Non-government Organization PMU Project Management Unit PI Principal Investigator TRC Technical Review Committee UPHSDP Urban Primary Health Care Services Delivery Project UN United Nations UHS Urban Health Survey UPPR Urban Partnerships for Poverty Reduction UHDSS Urban Health and Demographic Surveillance System UNFPA United Nations Population Fund

9 Summary of Key Findings and Implications

The population of Bangladesh is expected to increase from 158 million in 2014 to roughly 185 million by 2030 (UN 2014); almost all of that growth will occur in urban areas. It has also been estimated that Bangladesh will be more urban than rural by the middle of this century; more than a third of these urban residents will dwell in slum settlements.

To address the urban health challenge, the Government of Bangladesh with assistance from donors (ADB, Embassy of Sweden, and UNFPA) has been implementing the Urban Primary Health Care Services Delivery Project (UPHCSDP). The ultimate aim of the UPHCSDP is to improve health status of the urban poor, especially women and children.

The overall objective of the Operations Research (Service Package No. S-4.1) is to set up a Health and Demographic Surveillance System (HDSS) in selected slums of Dhaka (North and South) and Gazipur City Corporations. In fact, the baseline population and socioeconomic census is a pre-requisite where a HDSS is to be set up. The specific objective of the baseline census is to collect data on the following:

 Demographic characteristics (each individual)  Socioeconomic data (individual and household level)  Migration characteristics (household head)

Main findings of the baseline population and socioeconomic census are reported below (see Appendix A: Key Findings- Baseline Population and Socioeconomic Census, 2015-16):

 31.6% population was below age 15 years, while 2.6% at age 65 or more years.  Family size was 3.8.  82.3% households were headed by males.  91% slums were built on government lands.  67.9% occupants were tenants.  81.6% households possessed one bedroom; mean dwelling area was 119.4 sq. ft.  Roof material was mostly tin (94.0%), while about 70% wall material was tin; 88% floor materials were brick/cement.  About 95% households used pipe water for drinking; 92% households shared source of drinking water.  30% households had sanitary latrine flash to sewerage/septic tank, while 60% households had sanitary latrine flash to elsewhere; 90% households shared latrine.  Use of electricity as a source of light was universal (99.6%).  Slightly over 50% households used gas from gas line for cooking and 35% used solid fuel; 60% household’s shared cooking place.  For about 50% cases, garbage was dumped in open space outside the house, while for 47.2% cases garbage kept at home or dumped in the bin outside the home.

10  For about 40% cases, garbage was collected daily, while for 37% cases garbage was never collected.  Among adult (aged 15 or more years), 36.2% males and 42.3% females did not have any schooling.  Among children (aged 6-14 years), 14.1% boys and 8.9% girls did not have any schooling.  Among aged 8 or more years, 73.5% males were involved in income generating activities compared to 39.6% among females.  Most households had electric fan (96%), and mobile phone (85%). About 60% households had television and khat.  Mean household expenditure (total) was Taka 11,981 during last month; about 50% households spent Taka 5,000-9,999 during last month.  Mean household expenditure on food was Taka 6,291 during last month; about 65% households spent Taka 5,000-9,999 during last month.  Mean expenditure on education was Taka 604 during last month; 58% households did not spend any money on education during last month.  Mean expenditure on health was Taka 1,276 during last month; 35% households did not spend any money on health during last month.  Mean saving was Taka 527 during last month; majority of the households (72%) were unable to save any money during last month.  For 35% cases, the household heads migrated 20 years or more ago, followed by 14% migrated within the last 5 years; 8.6% did not migrate (since birth).  The majority of household heads migrated for work (62.4%), followed by 19.9% migrated to join family.  50% household heads migrated from Dhaka division, while 20% from Barisal division.

For establishing HDSS in a defined geographical area, a baseline population and socioeconomic census is essential, as such data is used as a basis for identifying subsequent events (birth, death, migration, etc.) as well as for adjusting denominator (person-year) for calculating rates/ratios of various population and health indicators. In fact, adjusted baseline census is also used as a sampling frame for designing cross-sectional as well as longitudinal studies. Moreover, HDSS platform provides tools/data for monitoring and evaluating the impacts of various social, economic and health interventions.

11 Chapter One Introduction

1.1 Background of the Project

As the majority of the world’s population now lives in urban areas, one of the key 21st century challenges in population health is the challenge of improving the global urban condition (Mehta 2004; Clos 2016). According to the United Nation’s projection (UN 2014), the world’s urban population will increase by about 1.3 billion by 2030, while the rural population will almost remain same. This shift is largely the result of a rapid global urbanization process that has been underway for more than two centuries. In fact, more than 90% of the world’s urban population growth by 2030 will be in the least developed regions.

According to United Nation’s estimate, the population of Bangladesh will increase from 158 million in 2014 to roughly 185 million by 2030 (UN 2014); bringing the urban population from about 50 million in 2014 to nearly 83 million. It is also estimated that Bangladesh will be more urban than rural by the middle of this century (Figure 1.1.1; more than one third of these urban residents will dwell in slum settlements.

Fig 1.1.1: Urban and Rural Population: Middle Income Countries and Bangladesh, 1950- 2050

120

100 Middle-income countries(urban) Middle-income countries(rural) 80 Bangladesh(urban) Bangladesh(rural) 60

40

20

0 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 0 5 5 6 6 7 7 8 8 9 9 0 0 1 1 2 2 3 3 4 4 5 9 9 9 9 9 9 9 9 9 9 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2

Source: World Urbanization Prospects: The 2014 Revision, United Nations, June, 2014.

Although urbanization has been found to be an effective engine of economic growth and socio-cultural development worldwide, there is increasing concern about the effect of

12 expanding cities, principally on human health, livelihood and environment, especially when it takes place at the pace as rapid as in Bangladesh. The growth of urban population in Bangladesh has mainly occurred through migration of the rural poor, and this has made the task difficult for the government to provide employment, services, and social benefits; unfortunately, urbanization does not equate to an increase in standard of living. Rapid urban growth has made heavy demand on urban utilities and services1, and the worst negative consequence is in the form of degradation of the urban environment; this will have long-term health consequences.

Bangladesh, although has witnessed remarkable progress over the last few decades in health and population indicators, significant disparities exist within urban areas, between slum and non-slum dwellers with respect to health, nutrition, housing, water and sanitation (Afsana & Wahid 2013; NIPORT 2015; Roy et al. 2014; Ahmed, Islam, Bhuiya 2015). In a recent article (Chowdhury et al. 2013), it was concluded that although an exceptional improvements in under-five survival, life expectancy, immunization coverage, and tuberculosis control, but the nation still faces considerable problems of poverty and malnutrition, and this is being exacerbated by an evolving set of 21st-century challenges (e.g., massive and rapid urbanization, an upsurge in chronic and non-communicable diseases, and increasing vulnerability to climate change).

For an understanding of the nature of problems facing by the slum dwellers, and for monitoring their trends, a systematic collection of population, health and socioeconomic data is a pre-requisite for dealing with these challenges. Currently, available data is necessary but not sufficient for an understanding of the problems prevailing in the slums for tackling such challenges.

1.2 Objective of the Study

The overall objective of the Operations Research (Service Package No. S-4.1) is to set up a Health and Demographic Surveillance System (HDSS) in selected slums of Dhaka (North and South) and Gazipur City Corporations. In fact, the baseline population and socioeconomic census is a pre-requisite where a HDSS is to be set up (i.e. data collection of Health and Demographic Surveillance System will began immediate after the baseline census). The specific objective of the baseline census is to collect data on the following:

 Demographic characteristics (each individual)  Socioeconomic data (individual and household level)  Migration characteristics (household head)

1 For example, electricity, gas, water, sanitation, sewerage, garbage disposal, transport and social services.

13 1.3 Organization of the Report

The report is divided into seven chapters including the introduction. The Chapter Two discusses the methods and procedures, while the main report starts from Chapter Three. Chapter Three discusses the population characteristics including household size and type, and dependency ratio. Chapter Four narrates the living conditions and Chapter Five deals with socioeconomic condition. Chapter Six deals with migrants’ characteristics (household head). Chapter Seven deals with the challenges to establish HDSS in slum settlements.

1.4 Funding Sources and Technical Support

Funding for the study was provided by the Government of the People’s Republic of Bangladesh, Ministry of Local Government, Rural Development and Cooperatives (PMU, UPHCSDP, Local Government Division), and Embassy of Sweden; technical support was provided by Asian Development Bank, and UNFPA (see Appendix B: Member of Technical Review Committee).

14 Chapter Two Methods and Procedures

2.1 Selection of Slums

In the census of slum Areas 2014, a total of 13,938 slums were counted covering all cities and other urban areas of Bangladesh (for details, see BBS 2015; and also, Appendices C.1, C.2 and C.3). Out of 13,938 slums, 33.62% were counted in Dhaka North (11.80%), Dhaka South (12.59%), and Gazipur (9.23%) City Corporations. During the census of slums, 22,27,754 populations were counted and of these populations, 11,85,875 (53.2%) lived in big slums (100 or more households).

After extensive field visits2, relatively big slums were selected, as big slums would be convenient for the female Field Workers (travel time, security, etc.) to collect data for the Health and Demographic Surveillance System. As most of the slums in Dhaka South City Corporation are small in size, it was decided to select more slums from Dhaka North City Corporation than Dhaka South City Corporation (Figure 2.1.1: Location of Slums: Dhaka North, Dhaka South and Gazipur City Corporations). So, the baseline population and socioeconomic census data would reflect the conditions of relatively big slums.

In Dhaka North City Corporation, slums were selected from Banani (9,745 households from Korail slum), and from Mirpur (6,230 households from Bhola, Molla and Duaripara slums).

In Dhaka South City Corporation, slums were selected from Dhalpur (2,046 households from Pura, Driver, Nubur, City Palli, Power House, and Mannan slums), and from Shayampur (2,385 households from Dhaka Mach Colony, Monsur Beel/Nama Para, and Rail Line slums).

In case of Gazipur City Corporation, slums were selected from Tongi (3,133 households from Bank Field, Hazi Mazar, Nishad Nagar and Kalabagan slums), and from Ershad Nagar (7,318 households from Ershad Nagar slum).

2.2 Concepts and Definitions

Concepts and definitions followed during the household listing and baseline population and socioeconomic census are described below:

Slum: A slum is a cluster of compact settlements of 5 or more households which generally grow very unsystematically and haphazardly in an unhealthy condition and atmosphere on government and private vacant land. Slums also exist on the owner based household premises and generally have the following six characteristics (for detail, see BBS 2015):

2As well as reviewing the data file received from the Bangladesh Bureau of Statistics ‘Census of Slum Areas and Floating Population-2014’ (BBS, 2015).

15 a) Structures of slums are generally very small such as jhupri, tong, tin-shed, semi-pucca structures and dilapidated buildings; b) Population density and the concentration of structures are very high; c) Slums generally grow on government, semi-government land, private vacant land, abandoned building/houses, and slopes of hill or rail-line and road sides; d) In slum areas, water supply is insufficient and unsafe, sanitation systems are quite inadequate and very unhygienic environment; e) Lighting and road facilities are very inadequate or not at all in the slum areas; f) Socioeconomic status of the slum dwellers is very low, and dwellers are generally engaged in informal non-agricultural jobs.

Fig 2.1.1: Location of Slums: Dhaka North, Dhaka South and Gazipur City Corporations

Health and Demographic Surveillance System: The Health and Demographic Surveillance System is a methodological approach to monitoring demographic and health outcomes in a registered and defined population living in a confined geographic area (INDEPTH Network 2002). The information collected at a minimum include vital events (births and deaths) and in- and out-migration. The HDSS starts with an initial census of the population living in

16 defined geographical areas, followed by regular household visits by Field Workers to update information on births, deaths, and migrations. After the initial census, one can only become an HDSS member through birth to a registered member or through in-migration, and one can cease being a member either through death or through out-migration.

Household: A household consists of one or more people who live together and share meals from a common cooking pot, and can identify one member as head of the household.

De jure Population: Information recorded in the baseline census followed de jure population definition, i.e. the person who usually lives in the household.

Resident: A person residing in the surveillance area permanently or continuously for at least six months is considered to be a resident. A person who resides outside the study area, but returns to his/her home in the HDSS area at least once a month and stays overnight, is also considered a resident.

Bari: A cluster of households where owner of these houses is usually the same and the tenants use a common space or facility.

Migrant: A household member is defined as migrant whose place of birth is different from their current place of residence.

Household Types: The following instructions were followed to categorise: i. Single-Person Households ii. One Generation Households Head and wife/husband Head and brother/sister Head, wife/husband and brother/sister. iii. Two-Generation Households Head, wife/husband and unmarried children. Head, wife/husband and married/unmarried children Head, married/unmarried children. Head, wife/husband and father/mother Head, brother/sister and father/mother Head, wife/husband, brother/sister and father/mother Head and father/mother

IV. Three-Generation Households Head, wife/husband, unmarried children and father/mother Head, wife/husband, unmarried/married children and father/mother Head, wife/husband, unmarried/married children and father/mother, son's wife, daughter's husband and grand-children. v. Other Households Households including non-relatives (i.e. tutor, cousins, nephews, nieces, servant)

17 Sex Ratio: The sex ratio is the ratio of males to females in a population (Male/Female*100).

Dependency Ratio: The dependency ratio is a measure showing the number of dependents (aged zero to 14 and over the age of 65), to the total population (aged 15 to 64). It is also referred to as the ‘total dependency ratio’. Dependency ratio is calculated with the formula: 100 Px/P15-64 where Px is the Population in age group x.

Samity: Samity means a committee, society, or association.

Mohajan: Mohajan is used here as a moneylender.

Occupation: Those of age 8 years or more were asked their occupations (paid job). Primary occupation depends on the respondent’s answer. For example, self-employed means a person makes wage on their own venture, like cow-rearing, mat-weaving and marketing, sewing clothes by oneself, etc. If a person gets monthly salary and if the respondent replies that he/she is doing a job, then it is to be coded as ’Employment’; confirming that whether the employment is public or private.

Note: If a person gets paid from more than one job then record the most-timed job as the primary occupation.

Education: Type: Ask the respondents in which type of school they are studying/have studied, like public, private, NGO, or religious school. Years of Schooling: Completed years of schooling was recorded.

Note: The education related question is not applicable for under 5 years’ children. School means any kind of formal educational institution. If someone says he/she has read up to class 5, then they will be asked if they passed the final exam of class 5. If yes, the code will be 5; otherwise, it will be 4. If no class/grade is found, then write “00”. in case of ‘Maktab’, education was recorded as no schooling.

Violence: Any kind of violent behavior, like attacking, beating, stabbing, destruction, etc. Robbery: If caught in any kind (in-house/external) of mugging or hijacking, then this code is to be used. Theft: This could be any kind (in-house/external) of stealing or burglary. Kidnapping: To take somebody away by force and hold him/her prisoner, for money and any demand. Sexual Harassment: Sexual harassment or unwanted sex-related behavior means to perform sexual intercourse with someone by force, or to tease/gesture for doing so.

2.3 Recruitment and Training of Field Workers

Initially, Field Research Coordinator, Computer Programmer and three Field Research Assistants were recruited. Subsequently, female Field Workers were recruited before the field work began; initially 12 Field Workers were recruited for household listing and subsequently increased to 22. One of the criteria for selecting female Field Workers for a particular area was the proximity of the worker’s residence to the field site. This would help

18 the Field Workers to visit the household beyond office hours, if the respondents are not available during daytime.

For household listing as well as for baseline population and socioeconomic census, Field Research Coordinator and Field Research Assistants were trained first by the Principal Investigator (PI)/Co-Principal Investigators (Co-PIs). Subsequently, female Field Workers were trained by the Field Research Coordinator and Field Research Assistants under the guidance of PI.

For household listing, a short training (half-day) was organized. For baseline population and socioeconomic census, the duration of training was seven days: five days in office (training on questionnaires, mock interview, and use of Tab), and two days for field practice. Field Workers were trained on data collection instrument, data collection device, and on interviewing skills and administering the consent form. The training on data collection device (use of Tab) was organized by the Computer Programmer.

2.4 Mapping and Household Listing

Initially, we collected existing maps from various sources for our study areas. After reviewing these maps, the slum (i.e., Korail) was divided into areas (for example, Bowbazar). The areas are identified primarily based on communities, and demarcated by physical landmarks. After mapping, household listing started from a suitable location (one Field Worker completed about 150 households per day). During household listing, the Field Workers assigned bari number (wrote bari number on the door), recorded name of house- owner (bariwala), and name of household head as well as household size. At the time of listing, the respondent was either an adult household member or a neighbour (household listing took about 3 weeks).

2.5 Questionnaires: Baseline Population and Socioeconomic Census

During baseline population and socioeconomic census, two types of structured questionnaires were administered for each household:

Individual member: Data were collected on age, sex, marital status, education (5 years or more), occupation (8 years or more), desire for child (currently married women of age 15- 49), and household head’s migration (see Questionnaire, Appendix E.1: Baseline Population and Socioeconomic Census – 2015-16 (All HHs)).

Household-level: Data were collected on possessions of household items, construction materials used for roof, wall and floor of the main dwelling, source of drinking water, type of latrine, fuel for cooking, sharing water source, latrine and cooking place, garbage disposal, ownership of land and house, number of dwelling and dwelling area. Data were also collected on membership of NGO/samity, and whether loan received, violence, robbery, theft, kidnapping, and sexual harassment and care of under-five, if mothers work outside the home. However, some household-level information (ownership of land and house, possession of items) were collected for each household and some information were collected from 10% households only (see Questionnaire, Appendix E.2: Baseline Socioeconomic Census – 2015-16 (Sample HHs)).

19 The questionnaires were prepared by the Principal Investigator (PI) and Co-Principal Investigators (Co-PIs); and subsequently, approved by the Ethical Review Committee of icddr,b; however, these questionnaires were pre-tested before data collection began. In fact, pre-testing of questionnaires was done by three female Field Workers under the guidance of PI and Field Research Coordinator. Feedbacks received from the field test were reviewed by the PI and Co-PIs, and useful suggestions were incorporated in finalizing the questionnaires.

2.6 Field Work- Baseline Population and Socioeconomic Census

The data collection for baseline population and socioeconomic census began from a suitable location of each female Field Workers’ assigned area. For finding a bari, the Field Workers also carried printouts of the household listing. Once a bari was identified, the Field Workers entered the slum name, area name and bari number into the Tab, and verified records with the printout; once confirmed, the household identification number was assigned into the Tab, and the Field Workers also wrote the household identification number on the door.

After assigning the household identification number, the Field Workers collected demographic information and household level socioeconomic data. As many women work outside home, the Field Workers had to visit these households during lunch time or in the evening or during a weekly holiday to collect the data. For collecting baseline census data, the Field Workers at first selected the respondent (either head of household or spouse or any adult household member of age 18 years or more) and got signed an informed consent form, if they agreed to provide information.

Each day a Field Worker completed about 40 households and submitted their completed work (on memory card) to their supervisor every week. After receiving the memory card, the supervisor used to transfer the data to his/her laptop and performed the basic checking of these data. The supervisor subsequently sent these data to the Field Research Coordinator/Computer Programmer through email (as attachment) for further editing and updating the master database. This phase of data collection (household listing, and baseline population and socioeconomic census) took about 4 months (September 15, 2015 to January 15, 2016).

2.7 Data Management

The data were collected using portable devices, and data collection programs were developed accordingly (initially for household listing and then the baseline population and socioeconomic census). The master database is a relational one and is managed in MySQL server. In the portable device, SQLite database was installed in back-end and Android Java in front-end. Some of the consistency checks were incorporated to the data collection program (range checks, consistency/logical checks); however, some logical checks were done at the office after loading/merging the data files.

20 2.8 Quality Control/Security

Field Research Assistants and Field Research Coordinator were responsible for assessing the day-to-day data quality. In fact, Field Research Assistants were responsible to monitor the data collection by the female Field Workers as well as to enter few records independently into his/her Tab (listening Field Workers interview). The Field Research Assistants were also responsible to re-interview 2% households per day. After receiving the data from the field, the Computer Programmer edited the data and updated the master database.

To maintain security and confidentiality of the data, the data server was restricted by a security password and access was given only to a selected person. In addition, a backup of the data file was kept in different locations and were updated periodically.

21 Chapter Three Population Characteristics

Key Findings:  In these slums, 118,238 population counted, while 58,461 males, 59,758 females, and 19 transgender people.  31.6% population was below age 15 years, while 2.6% in age 65 or more years.  Family size was 3.8.  82.3% households were headed by male, while 18% were headed by female.

This chapter describes the demographic characteristics of the population, including age, sex, dependency ratio, household type and size, and marital status by slum locations. The census followed a de jure population definition; recorded individuals who were the usual residents of households. To be a resident, a person has to reside in the surveillance area permanently or continuously for at least six months.

3.1 Population Size

Table 3.1.1 shows the distribution of households as well as the distribution of population by slum locations. According to de jure population definition, 30,857 households were counted in these slums with a population of 118,238. Out of 118,238 population, 35.3% lived in Tongi, followed by Korail (30.8%), Mirpur (19.5%), and fewer lived in Dhalpur/Shayampur (14.4%). The average household size was 3.8 and did not vary much across slum locations (3.7 to 4.0).

Table 3.1.1: Distribution of Households and Distribution of Population by Slum Locations

Household Population Mean Location Number Per cent Number Per cent (HH size) Korail 9,745 31.6 36,422 30.8 3.7 Mirpur 6,230 20.2 23,049 19.5 3.7 Dhalpur & Shayampur 4,431 14.3 16,981 14.4 3.8 Tongi 10,451 33.9 41,786 35.3 4.0 Total 30,857 100 118,238 100 3.8 Note: HH=Household

3.2 Age and Sex Characteristics

Table 3.2.1 shows the distribution of population by five-year age groups and sex. Slightly more females than males lived in the slum (59,758 vs. 58,461) yielding a sex ratio of 97.8. However, sex ratios were not same in different age groups. For population below 15 years

22 and for population of age 30 years or more, there were more males than females but for population between 15 and 29 years, there were more females than males.

Table 3.2.2 shows the distribution of population (per cent) by broad age groups and slum locations. The population was young, 31.6% were below 15 years of age, 64.1% were between 15 and 59 years, and very few were 60 years of age or more (4.4%). A similar pattern of age distribution also held across slum locations.

Table 3.2.1: Distribution of Population by Five-Year Age groups and Sex

Age Number Per cent (years) Both Male Female Sex ratio Both Male Female 0-4 10,877 5,545 5,332 104.0 9.2 9.5 8.9 5-9 13,889 6,973 6,916 100.8 11.8 11.9 11.6 10-14 12,435 6,259 6,176 101.3 10.6 10.7 10.3 15-19 13,829 6,213 7,616 81.6 11.7 10.5 12.7 20-24 11,989 4,872 7,117 68.5 10.1 8.3 11.9 25-29 13,636 6,567 7,069 92.9 11.5 11.2 11.8 30-34 9,365 4,854 4,511 107.6 7.9 8.3 7.6 35-39 9,143 4,667 4,476 104.3 7.7 8.0 7.5 40-44 6,147 3,371 2,776 121.4 5.2 5.8 4.7 45-49 5,504 2,836 2,668 106.3 4.7 4.9 4.5 50-54 3,832 2,043 1,789 114.2 3.2 3.5 3.0 55-59 2,373 1,319 1,054 125.1 2.0 2.3 1.8 60-64 2,154 1,178 976 120.7 1.8 2.0 1.6 65-69 1,170 687 483 142.2 1.0 1.2 0.8 70-74 1,056 626 430 145.6 0.9 1.1 0.7 75-79 304 188 116 162.1 0.3 0.3 0.2 80+ 516 263 253 104.0 0.4 0.5 0.4 Total 118,219 58,461 59,758 97.8 100 100 100 Note: Transgender people were excluded (19)

3.3 Dependency Ratio

Table 3.3.1 shows the dependency ratios by slum locations. The overall dependency ratio was 51.6; however, the dependency ratio varied across the slums- 55.6 in Dhalpur/Shayampur and 46.6 in Mirpur. The dependency ratio for young was 47.7, while for old, the ratio was 3.9. For young (44.2 to 51.9) and for old (2.4 to 6.0), the dependency ratios varied slightly across slum locations.

23 Table 3.2.2: Distribution of Population (per cent) by Broad Age Group and Slum Locations

Dhalpur & Age Korail Mirpur Tongi Total Shayampur (year) (N=36,422) (N=23,049) (N=41,786) (N=118,238) (N=16,981) <15 33.2 30.2 33.3 29.9 31.5 15-59 63.6 66.9 62.3 63.8 64.1 60-64 1.6 1.3 2.0 2.3 1.8 65+ 1.6 1.6 2.4 4.0 2.6 Total 100 100 100 100 100

Table 3.3.1: Dependency Ratios by Slum Locations Dhalpur & Age Korail Mirpur Tongi Total Shayampur (year) (N=36,422) (N=23,049) (N=41,786) (N=118,238) (N=16,981) <15 12,092 6,952 5,662 12,497 37,203 15-64 23,732 15,722 10,910 27,625 77,989 65+ 598 375 409 1,664 3,046 Dependency ratio Total 53.5 46.6 55.6 51.3 51.6 Young 51.0 44.2 51.9 45.2 47.7 Old 2.5 2.4 3.7 6.0 3.9 Note: Dependency ratio is calculated with the formula: 100 Px/P15-64 where Px is the Population in age group x.

3.4 Household Size and Type

Table 3.4.1 shows the distribution of households by type and sex of household head. Out of 30,857 households enumerated in these slums, 82.3% were headed by males and 17.7% were headed by females. 57.8% of these households belonged to two-generation, followed by three-generation (20.1%), while very few were single-person households (2.7%). Such household types differ for male- and female-headed households. In fact, two-generation households are more among male headed households (62.6%), while three generation households are more among female headed households (40.2%).

24 Table 3.4.1: Distribution of Households by Type and Sex of Household Heads

Number Per cent Type Female Male Total Female Male Total Single person 630 220 850 11.7 0.9 2.7 One generation 378 4,200 4,578 6.9 16.5 14.8 Two generations 1,909 15,917 17,826 35.0 62.6 57.8 Three generations 2,193 4,005 6,198 40.2 15.8 20.1 Others 340 1,065 1,405 6.2 4.2 4.6 Total 5,450 25,407 30,857 100 100 100

3.5 Marital Status

Information on marital status was collected from those who were 12 years or more. Table 3.5.1 shows the distribution of population (age 12 or more) by marital status and sex. Most of the population was currently married (67.6%), followed by never married (19.2%), while the rest of them were either separated or divorced or widowed (13.2%). There were slightly more currently married among males than females (70.0% vs. 68.8%), while widowed (3.6% vs. 0.3%), separated (1.2% vs. 0.3%) and divorced (8.4% vs. 0.6%) were more among females than males.

Table 3.5.1: Distribution of Population+ by Marital Status and Sex

Number Per cent Marital Status Both Male Female Both Male Female Currently married 60,726 30,317 30,409 68.8 70.0 67.6 Never married 21,096 12,462 8,634 23.9 28.8 19.2 Widowed 1,754 131 1,623 2.0 0.3 3.6 Separated 678 124 554 0.8 0.3 1.2 Divorced 4,024 257 3,767 4.5 0.6 8.4 Total 88,278 43,291 44,987 100 100 100 Note: +Age 12 or more; almost all were Muslims (99.2%) with negligible per cent were Hindus and Christians (0.8%).

25 Chapter Four

Living Condition

Key Findings:

 These slums were mainly built on government land (91%), while in Mirpur, 31% slums were on private land.  67.9% occupants were tenant, while 31.6% were owner of the house.  82% households possessed one bedroom; mean dwelling area was 119.4 sq. ft.  Roof material was mostly tin (94.0%), while about 70% wall material was tin. 88% floor material was brick/cement.  About 95% households used pipe water for drinking; 92% households shared source of drinking water.  32% households had sanitary latrine flash to sewerage/septic tank, while 60% households had sanitary latrine flash to elsewhere; 90% households shared

26 latrine.  Use of electricity as a source of light was universal (99.6%).  Slightly over 50% households used gas for cooking and 35% used solid fuel; 60% households shared cooking place.  For about 50% cases, garbage was dumped in open space outside the house, while for 47.2% cases garbage kept at home or dumped in bin outside the house.  Garbage was collected daily for about 40% cases, while for 37% cases garbage was never collected.

This chapter describes the ownership of land and dwelling, housing condition, construction material used for dwelling, water and sanitation, source of light and fuel for cooking, and garbage disposal system by slum locations. These information were collected for 10% systematically selected households, except ownership of land and dwelling; those covered all households of the surveillance area.

4.1 Ownership of Land and Dwelling

An inquiry was made to know about ownership of land as well as ownership of the dwelling. Table 4.1.1 shows the distribution of households (per cent) by ownership of land and slum locations. Slums were mostly built on government land (90.7%), while 9.3% were built on private land. Ownership of land varied across slum locations; 100% land in Korail and Tongi were owned by the government, while 78.8% land in Dhalpur/Shayampur, and 69.3% land in Mirpur were owned by the government.

Table 4.1.1: Distribution of Households (per cent) by Ownership of Land and Slum Locations

Dhalpur & Ownership Korail Mirpur Shayampur Tongi Total (N= 9,745) (N= 6,228) (N=4,427) (N=10,449) (30,857) Head/other resident 0.0 0.1 1.0 0.0 0.2 Landlord 0.0 30.6 20.2 0.0 9.1 Government 100.0 69.3 78.8 100.0 90.7 Total 100 100 100 100 100

Table 4.1.2 shows the distribution of households (per cent) by ownership of dwelling and slum locations. 67.9% occupants were tenants, while 31.6% occupants were owner of dwelling. There were more tenants in Mirpur (87.4%), followed by Dhalpur/Shayampur and Korail (70%-73%), while fewer tenants were in Tongi (51.6%). Consequently, 48.2% occupants were owner of the dwelling in Tongi, followed by Dhalpur/Shayampur and Korail (25%-29%), and fewer owners were in Mirpur (12.4%).

27 Table 4.1.2: Distribution of Households (per cent) by Ownership of Dwelling and Slum Locations

Dhalpur & Ownership Korail Mirpur Shayampur Tongi Total (N=9,745) (N=6,230) (N=4,431) (N=10,451) (30,857) Head/other member 29.1 12.4 25.2 48.2 31.6 House owner/Bariwala 70.5 87.4 72.8 51.6 67.9 Other 0.4 0.2 2.1 0.2 0.5 Total 100 100 100 100 100 Note: Owner (Head/other member); Tenant (House owner/bariwala)

4.2 Housing Condition

Inquiry was made on the number of dwelling as well as about length and breadth of the dwelling(s), and was recorded after physical verification. Table 4.2.1 shows the distribution of households (per cent) by number of dwelling and slum locations. 81.6% of the households possessed one bedroom, followed by two bedrooms (14.7%), while households with three or more bedrooms were negligible (3.7%); mean number of dwelling was 1.2. When number of bedroom was examined across slums, one-bedroom households were more in Korail and Mirpur (90%), followed by Dhalpur/Shayampur (83.6%) and fewer in Tongi (67.9%). Two bedroom houses were more in Tongi (24.2%) and fewer in Korail and Mirpur (8-10%), while three or more bedroom houses were more in Tongi (7.9%) and negligible in other slums (1%- 2%); mean number of dwelling vary slightly across slum locations (1.1 to 1.4).

Table 4.2.1: Distribution of Households (per cent) by Number of Dwelling and Slum Locations Dhalpur & No. of Korail Mirpur Shayampur Tongi Total Dwelling (N=979) (N=667) (N=461) (N=1,006) (N=3,113) 1 88.9 90.3 83.6 67.9 81.6 2 9.8 8.0 14.5 24.2 14.7 3 1.1 1.4 1.7 7.6 3.4 4 0.2 0.3 0.2 0.3 0.3 Total 100 100 100 100 100 Mean 1.1 1.1 1.2 1.4 1.2

28 Table 4.2.2 shows the distribution of households (per cent) by dwelling area and slum locations. About 48% households possessed dwelling area for less than 100 sq. ft., followed by 31.4% for 100-149 sq. ft., and 21.1% for 150 or more sq. ft.; mean dwelling area was 119.4 sq. ft. When the mean dwelling area was examined by slum locations; in Dhalpur/Shayampur (147.3 sq. ft.), dwelling area was bigger than Tongi (135.4 sq. ft.), Mirpur (117.6 sq. ft.) and Korail (90.9 sq. ft.).

Table 4.2.2: Distribution of Households (per cent) by Dwelling Area and Slum Locations

Dhalpur & Area (sq. ft.) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) < 50 18.8 3.9 1.7 5.5 8.8 50-99 50.6 42.4 21.3 32.6 38.7 100-149 20.6 36.6 44.9 32.3 31.4 150-199 6.1 8.0 15.4 11.5 9.6 200+ 3.9 9.1 16.7 18.1 11.5 Total 100 100 100 100 100 Mean (sq. ft.) 90.9 117.6 147.3 135.4 119.4

4.3 Construction Material Used for Dwelling

Information on construction material of roof, wall, and floor of the largest dwelling was recorded after physical verification. Table 4.3.1 shows the distribution of households (per cent) by construction material for roof and slum locations. For roof, mostly tin was used (94.0%) followed by wood/bamboo (3.1%) and brick/cement (2.9%). However, roof materials did not vary much across slum locations.

Table 4.3.2 shows the distribution of households (per cent) by construction material for wall and slum locations. 70.4% wall was made of tin and 29.1% was made of brick/cement. However, wall material varied across slum locations. 90.7% wall was made of tin in Korail, followed by Mirpur (75.3%), Dhalpur/Shayampur (55.8%) and Tongi (54.1%). About 46% wall was made of brick/cement in Tongi, followed by Dhalpur/Shayampur (42.1%), Mirpur (24.7%) and fewer in Korail (9.1%).

29 Table 4.3.1: Distribution of Households (per cent) by Construction Material of Roof and Slum Locations Dhalpur & Roof material Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Wood/bamboo 5.7 1.2 7.2 0.2 3.1 Brick/cement 1.9 0.9 8.2 2.7 2.9 Tin 92.4 97.9 84.6 97.1 94.0 Total 100 100 100 100 100

Table 4.3.2: Distribution of Households (per cent) by Construction Material of Wall and Slum Locations Dhalpur & Wall material Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Wood/bamboo 0.2 0.0 2.1 0.3 0.5 Brick/cement 9.1 24.7 42.1 45.6 29.1 Tin 90.7 75.3 55.8 54.1 70.4 Total 100 100 100 100 100

Table 4.3.3 shows the distribution of households (per cent) by construction material for floor and slum locations. Floor material was mostly brick/cement (88%), followed by wood/bamboo (7.8%) and earth/katcha (4.2%). Floor material varied slightly across slum locations. About 90% floor materials of Korail, Mirpur and Dhalpur/Shayampur were brick/cement, while it was 82.5% in Tongi; 18% floor were either wood/bamboo or earth/katcha in Tongi, followed by Dhalpur/Shayampur, Mirpur and Korail (9%-10%).

Table 4.3.3: Distribution of Households (per cent) by Construction Material of Floor and Slum Locations Dhalpur & Floor material Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Earth/katcha 1.0 2.9 2.6 8.9 4.2 Wood/bamboo 8.3 6.5 7.2 8.6 7.8 Brick/cement 90.7 90.6 90.2 82.5 88.0 Total 100 100 100 100 100

30 4.4 Water and Sanitation

Inquiry was made on source of drinking water as well as type of latrine. These information were recorded after physical verification; it was also physically verified whether sanitary latrine was drained to septic tank/sewerage or somewhere else.

Table 4.4.1 shows the distribution of households (per cent) by source of drinking water and slum locations. About 95% households used pipe water for drinking, followed by tube well water (5.1%). Source of water did not vary much across slum locations. However, use of tube well for drinking water was more in Dhalpur/Shayampur (9.3%), followed by Korail (8.7%), and negligible use in Mirpur and Tongi (1-2%).

Table 4.4.2 shows the distribution of households (per cent) by those sharing water source and slum locations. About 91.9% households shared water source for drinking and it varied across slum locations. About 95% households shared water source in Korail, Mirpur and Dhalpur/Shayampur, followed by Tongi (84%); 37.4% shared among 10 or more households, 31% shared among 5-9 households, and 23.5% shared among 1-4 households.

Table 4.4.1: Distribution of Households (per cent) by Source of Drinking Water and Slum Locations Dhalpur & Source Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Pipe water 88.7 98.8 90.5 97.5 93.9 Tube well 8.7 1.2 9.3 2.2 5.1 Others 2.6 0.0 0.2 0.3 1.0 Total 100 100 100 100 100

Table 4.4.2: Distribution of Households (per cent) by Those Sharing Water Source and Slum Locations Sharing Dhalpur & (No. of Korail Mirpur Shayampur Tongi Total households) (N=979) (N=667) (N=461) (N=1,006) (N=3,113) 0 5.7 2.7 3.0 16.3 8.1 1-4 16.5 12.9 13.9 41.8 23.5 5-9 40.5 44.1 29.3 13.9 31.0 10+ 37.3 40.3 53.8 28.0 37.4 Total 100 100 100 100 100

31 Table 4.4.3 shows the distribution of households (per cent) by type of latrine and slum locations. About 30% households had sanitary latrine flash to sewerage/tank, while 60.9% households had sanitary latrine flash to elsewhere and 6.4% households had pit latrine without slab or hanging/open latrine. Types of latrine varied across slum locations. In Korail, sanitary latrine flash to elsewhere was common (75.6%), followed by Mirpur (65.5%) and Dhalpur/Shayampur and Tongi (41%-53%). However, pit latrine without slab and hanging/open latrine was more in Dhalpur/Shayampur (19.6%) and fewer in Korail (1.3%).

Table 4.4.4 shows the distribution of households (per cent) by those sharing latrine and slum locations. About 90% households shared latrine and it varied across slum locations. Over 95% households shared in Korail, Mirpur, and Dhalpur/Shayampur, while 78% shared latrine in Tongi. Among those shared latrine, 31.7% shared latrine among 10 or more households, 32.4% shared latrine among 5-9 households and 26.2% shared among 1-4 households.

Table 4.4.3: Distribution of Households (per cent) by Type of Latrine and Slum Locations Dhalpur & Type Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Sanitary(sewerage/tank) 22.6 24.8 36.8 35.9 29.5 Sanitary(elsewhere) 75.6 65.5 41.0 52.7 60.9 Ventilated(improved) 0.5 7.4 2.6 3.5 3.2 Pit latrine(no slab) 1.1 1.8 11.1 2.4 3.2 Hanging/open 0.2 0.5 8.5 5.5 3.2 Total 100 100 100 100 100

Table 4.4.4: Distribution of Households (per cent) by Those Sharing Latrine and Slum Locations Sharing Dhalpur & (No. of Korail Mirpur Shayampur Tongi Total households) (N=979) (N=667) (N=461) (N=1,006) (N=3,113) 0 4.3 2.7 3.7 22.3 9.7 1-4 17.7 13.0 20.0 46.0 26.2 5-9 44.4 43.2 34.9 12.4 32.4 10+ 33.6 41.1 41.4 19.3 31.7 Total 100 100 100 100 100

32 4.5 Source of Light and Fuel for Cooking

Table 4.5.1 shows the distribution of households (per cent) by source of light and slum locations. Use of electricity as a source of light was almost universal (99.6%) and did not vary across slum locations.

Table 4.5.2 shows the distribution of households (per cent) by type of fuel for cooking and slum locations. Slightly over 50% households used gas for cooking, followed by wood (34.9%); while use of gas-cylinder (1.4%), kerosene (2.4%), electricity (3.8%) and others (4.0%) were negligible. Type of fuel for cooking varied considerably across slum locations. In Korail and Mirpur, 85%-98% households used gas from gas line, followed by Dhalpur/Shayampur (25.8%) and negligible use of gas in Tongi (2.1%). About 70% households used wood in Dhalpur/Shayampur and Tongi, while use of wood was 10.8% in Mirpur and negligible use in Korail (1.7%). In Tongi, use of electricity for cooking was high (10%), and almost nil in other slums.

Table 4.5.1: Distribution of Households (per cent) by Source of Light and Slum Locations Dhalpur & Source Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Electricity 99.6 99.8 100.0 99.3 99.6 Kerosene 0.4 0.2 0.0 0.7 0.4 Total 100 100 100 100 100

Table 4.5.3 shows the distribution of households (per cent) by those sharing cooking place and slum locations. About 60% households shared cooking place; however, sharing cooking place was more in Korail (95%) and fewer in Tongi (18%). Those households shared cooking place, 25% shared kitchen among 5-9 households, 20% shared among 1-4 households, while 15.9% shared among 10 or more households.

Table 4.5.2: Distribution of Households (per cent) by Type of Fuel for Cooking and Slum Locations Dhalpur & Type of Fuel Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Gas line 98.1 84.5 25.8 2.1 53.5 Wood 1.7 10.8 67.9 68.1 34.9 Gas cylinder 0.0 0.0 0.0 4.4 1.4 Kerosene 0.0 3.0 5.6 3.0 2.4 Electricity 0.2 1.7 0.7 10.0 3.8 Others 0.0 0.0 0.0 12.4 4.0 Total 100 100 100 100 100

33 Table 4.5.3: Distribution Households (per cent) by those Sharing Cooking Place and Slum Locations

Sharing Dhalpur & (No. of Korail Mirpur Shayampur Tongi Total huseholds) (N=979) (N=667) (N=461) (N=1,006) (N=3,113) 0 5.4 11.7 55.8 82.3 39.1 1-4 25.8 21.8 21.4 12.6 20.0 5-9 42.1 40.6 15.0 2.6 25.0 10+ 26.7 25.9 7.8 2.5 15.9 Total 100 100 100 100 100

4.6 Garbage Disposal

Inquiry was made on how garbage was dumped and how often garbage was removed. Table 4.6.1 shows the distribution of households (per cent) by garbage dumping system and slum locations. For about 50% cases, garbage was kept in open space outside the house, followed by kept garbage at home (30.3%), put garbage in bin outside the home (16.9%) and negligible per cent dumped garbage somewhere else (5.5%). Keeping garbage in open space outside the home did not vary much across slum locations (42%-55%). However, dumping system varied for those who kept garbage at home, 38.1% in Mirpur and 15.2% in Dhalpur/Shayampur; while dumping garbage in bin outside the home also varied across slum locations (6%-20%).

Table 4.6.2 shows the distribution of households (per cent) by frequency of garbage collection and slum locations. For about 40% cases garbage was collected daily, followed by 1-3 times in a week (18.3%), and 3-4 times a month (3.4%); for 36.5% cases garbage was never collected. In case of daily garbage collection, it varied across slum locations. In Mirpur, 84.4% cases garbage was collected daily, while only for 21.3% cases garbage was collected daily in Tongi. Where garbage was collected 1-3 times a week, it varied across slum locations. In Korail, 28.7% cases garbage was collected 1-3 times a week, followed by Tongi (24.8%) and Dhalpur/Shayampur and Mirpur (2%-5%).

Table 4.6.1: Distribution of Households (per cent) by Garbage Dumping System and Slum Locations Dhalpur & Dumping System Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Open space(outside) 44.0 42.0 55.3 50.4 47.3 At house 36.2 38.1 15.2 26.5 30.3 Bin outside house 19.5 15.4 6.5 20.0 16.9 Others 0.3 4.5 23.0 3.1 5.5 Total 100 100 100 100 100

34 Table 4.6.2: Distribution of Households (per cent) by Frequency of Garbage Collection and Slum Locations Dhalpur & Frequency Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) Everyday 24.9 84.4 61.0 21.3 41.8 1-3 times a week 28.7 2.3 5.0 24.8 18.3 3-4 times a month 1.0 0.0 0.8 9.2 3.4 Never collected 45.4 13.3 33.2 44.7 36.5 Total 100 100 100 100 100

35 Chapter Five Socioeconomic Condition

Key Findings:

 Among adult (aged 15 or more years), 36.2% males and 42.3% females did not have any schooling.  Among children (aged 6-14 years), 14.1% boys and 8.9% girls did not have any schooling.  Among aged 8 or more years, 73.5% males were involved in income generating activities compared to 39.6% among females. Dominant occupation among males were labourer (26.4%), student (14.5%), business (13.2%), service holder (11.7%), rickshaw/van puller (11.3%), and garment worker (10.3%); while among females, dominant occupations were housewife (35.7%), garment worker (19.1%), student (14.7%), domestic work (9.6%) and labourer (4.6%).  Most households had electric fan (96%), and mobile phone (85%). About 60% households had television and khat.  Mean household expenditure (total) was Taka 11,981 during last month; about 50% households spent Taka 5,000-10,000 during last month.

36  Mean household expenditure on food was Taka 6,291 during last month; about 65% households spent Taka 5,000-9,999 during last month.  Mean expenditure on education was Taka 604 during last month; 58% households did not spend any money on education during last month.  Mean expenditure on health was Taka 1,276 during last month; 35% households did not spend any money on health during last month.  Mean saving was Taka 527 during last month; majority of the households (72%) were unable to save any money during last month.

This chapter describes educational qualification, type of occupation, possession of items, household expenditure (total, food, education and health), and household’s saving. Information on education was collected for each individual aged five years or more. If an individual had more than one type of schooling, the most advanced one was considered. Completed year(s) of schooling was recorded, and in case of Maktab education, it was recorded as no schooling. Information on primary occupation (paid job) was collected for individual aged eight years or more. Information on expenditure and saving were collected during last month for 10% systematically selected households.

5.1 Educational Qualification

Table 5.1.1 shows the distribution of population (age 15 or more) by years of schooling and sex. The education level was low: 39.4% did not have any schooling, 22.3% completed 1-5 years of schooling, 15.1% completed 6-9 years of schooling, and 22.8% completed 10 or more years of schooling.

The level of schooling differed for male and female, more males had some schooling than females (63.8% vs. 57.7%). In fact, slightly more males were in 1-5 years of schooling category than females (23.2% vs. 21.5%), and in 10 or more years of schooling category (25.1% vs. 20.7%) but slightly more females than males were in 6-9 years (15.4% vs. 14.7%).

Table 5.1.2 shows the distribution (per cent) of children (age 6-14 years) by type of school and slum locations. About 12% children did not have any schooling, while 88% did go to school and completed at least one year of schooling. Those who did go to school, 29.4% were in private schools, 27% were in NGO schools, 25.4% were in government schools, and 6.7% were in religious schools. Type of school differed across slum locations; NGO schools were more in Korail and Mirpur (33%-42%), while fewer NGO schools were in Tongi (11.5%). Private schools were more in Tongi (43.8%) and fewer in Korail (20.7%), while government schools were more in Dhalpur/Shayampur (36.3.%) and fewer in Korail (18.1%).

37 Table 5.1.1: Distribution of Population+ by Years of Schooling and Sex

Years of Number Per cent Schooling Male Female Both Male Female Both No education 13,878 16,934 30,812 36.2 42.3 39.4 Primary incomplete 1,457 801 2,258 3.8 2.0 2.9 Primary complete 7,429 7,791 15,220 19.4 19.5 19.4 Secondary incomplete 5,634 6,161 11,795 14.7 15.4 15.1 Secondary complete 7,563 6,927 14,490 19.8 17.3 18.5 Higher secondary or more 2,015 1,373 3,388 5.3 3.4 4.3 Missing 315 26 341 0.8 0.1 0.4 Total 38,291 40,013 78,304 100 100 100 Note: +Age 15 or more

Figure 5.1.1 shows the distribution (per cent) of children (age 6-14 years) by type of school and sex. Among age 6-14 years, girls completed more schooling than boys (91.1% vs. 85.9%). Of those who completed schooling, more girls than boys, in NGO school (30.1% vs. 24.0%), private school (30.5% vs. 28.4%), and government school (26.8% vs. 23.9%); however, in religious schools (9.6% vs. 3.7%), there were more boys than girls.

Table 5.1.2: Distribution of Children+ (per cent) by Type of School and Slum Locations

Dhalpur & Type of Korail Mirpur Shayampur Tongi Total School (N=7,493) (N=4,353) (N=3,551) (N=7,824) (N=23,221) No education 13.8 10.7 12.1 9.4 11.5 Government school 18.1 26.7 36.3 26.7 25.4 Private school 20.7 22.6 24.5 43.8 29.4 NGO school 42.5 33.3 21.1 11.5 27.0 Religious school 4.9 6.7 6.0 8.6 6.7 Total 100 100 100 100 100 Note: +Age 6-14 years

38 Fig 5.1.1: Distribution of Children+ (per cent) by Type of School and Sex

35 30.5 30.1 30 28.4 26.8 24.0 25 23.9

20 14.1 15 9.6 10 8.9

5 3.7

0 No education Govt. Private NGO Religious Note: +Age 6-14 years Boy Girl

5.2 Occupation

Information on occupation was collected for individual aged eight years or more. Table 5.2.1 shows the distribution of population (age 8 or more) by occupation and sex. Among males, 73.5% were involved in income generating activities compared to 39.6% among females3. Other than no-work category (10.8% vs. 9.3%), dominant occupation among males were labourer (26.4%), student (14.5%), business (13.2%), service holder (11.7%), rickshaw/van puller (11.3%), and garment worker (10.3%); while among females, dominant occupations were housewife (35.7%), garment worker (19.1%), student (14.7%), domestic work (9.6%) and labourer (4.6%).

Table 5.2.2 shows the distribution (per cent) of population (age 8 years or more) by occupation and slum locations; some occupations vary considerably across slum locations. In fact, service holders were more in Dhalpur/Shayampur and Korail (11%-12%) and fewer in Mirpur and Tongi (3%-4%). Garment workers were more in Mirpur (24.7%), followed by Tongi (18.8%) and fewer in Dhalpur/Shayampur and Korail (4%-8%). Rickshaw/van pullers were more in Korail (8.5%), followed by Dhalpur/Shayampur and Mirpur (5%-6%) and fewer in Tongi (2.9%). Labourers were more in Dhalpur/Shayampur (23.4%), followed by Tongi and Mirpur (15.5%) and fewer in Korail (11.1%). Domestic workers (female) were more in Korail (10.3%), followed by Mirpur (5.9%) and fewer in Tongi and Dhalpur/Shayampur (1%-3%).

3If mother works for income generating activities, it is expected that mother will go outside the home. In our study, an inquiry was made to know who took care of under-five children, if mothers work outside the home. Out of 288 mothers identified with under-five children and mothers working outside, 41% reported that nobody took care of the under-five children, while for 41.3% cases the under-five children were looked after by relatives, and for 8% cases the under-five children were taken care of by siblings (for detail, see Appendix D.1).

39 Table 5.2.1: Distribution of Population by Occupation+ and Sex

Number Per cent Occupation Male Female Both Male Female Both Private service 4,944 1,172 6,116 10.5 2.4 6.4 Garment worker 4,847 9,296 14,143 10.3 19.1 14.8 Government service 580 253 833 1.2 0.5 0.9 Self-employed 297 595 892 0.6 1.2 0.9 Rickshaw/van puller 5,302 0 5,302 11.3 0.0 5.5 Business 6,237 894 7,131 13.2 1.7 7.4 Labourer (skill/un-skill) 12,445 2,224 14,669 26.4 4.6 15.3 House-wife 0 17,415 17,415 0.0 35.7 18.2 Domestic work (female) 0 4,667 4,667 0.0 9.6 4.9 Domestic work (male) 6 222 228 0.0 0.5 0.2 Student 6,822 7,149 13,971 14.5 14.7 14.6 No work 5,082 4,539 9,621 10.8 9.3 10.0 Other 572 321 893 1.2 0.7 0.9 Total 47,134 48,747 95,881 100 100 100 Note: +Age 8 or more; less than 0.1% was considered as ‘0’.

Table 5.2.2: Distribution of Population (per cent) by Occupation+ and Slum Locations Dhalpur & Occupation Korail Mirpur Shayampur Tongi All (N=29,096) (N=18,872) (N=13,576) (N=34,337) (N=95,881) Private service 11.0 3.6 8.3 3.2 6.4 Garment worker 8.4 24.7 4.1 18.8 14.8 Government service 0.2 0.3 4.2 0.3 0.9 Self-employed 0.6 0.2 2.7 0.9 0.9 Rickshaw/van puller 8.5 5.9 5.2 2.9 5.5 Business 7.7 6.6 6.2 8.2 7.4 Labour (skill/un-skill) 11.1 15.6 23.4 15.5 15.3 House-wife 16.2 15.6 19.1 20.9 18.2 Domestic work (female) 10.3 5.9 2.8 0.6 4.9 Domestic work (male) 0.7 0.0 0.0 0.0 0.2 Student 12.7 13.4 14.2 17.0 14.6 No work 11.4 7.4 8.5 11.0 10.0 Other 1.2 0.8 1.3 0.7 0.9 Note: +Age 8 or more

5.3 Household Possessions

Inquiries were made on ownership of articles; such as chair/table, dining table, khat, chawki, sofa set, almirah/wadrobe, radio, television, fridge, mobile phone, electric fan, watch/clock,

40 rickshaw/van, computer/laptop, and sewing machine. Damaged items were included, if these were repairable.

Table 5.3.1 shows the distribution of households (per cent) owning selected items by slum locations; some items vary slightly by slum locations Most households had electric fan (94- 97%), and mobile phone (82%-87%), followed by television (50%-70%) and khat (41%-71%), chawki (23%-55%), and almirah/wardrobe (15%-49%), chair/table, watch/clock, and fridge (8%-25%) and sewing machine (4%-10%).The households owning dining table or sofa set or radio or rickshaw/van or computer/laptop were exceptionally few (0.2%-3.5%).

In fact, khat was more in Dhalpur/Shayampur (71.0%) and fewer in Korail (41.1%), chawki was more in Korail (54.8%) and fewer in Dhalpur/Shayampur (23.1%), television was more in Tongi (70.3%) and fewer in Korail (50.5%); while almirah/wardrobe was more in Tongi (49.2%) and fewer in Korail (15.4%).

Table 5.3.1: Distribution of Households (per cent) Owning Selected Items by Slum Locations

Dhalpur & Asset Korail Mirpur Shayampur Tongi All (N=9,745) (N=6,230) (N=4,431) (N=10,451) (N=30,857) Chair/table 17.1 25.2 31.0 22.1 22.4 Dining table 0.6 1.9 0.8 1.8 1.3 Khat 41.1 58.1 71.0 68.8 58.2 Chawki 54.8 37.9 23.1 32.1 39.2 Sofa set 1.3 1.9 1.6 3.0 2.0 Almirah/wardrobe 15.4 27.6 29.2 49.2 31.3 Radio 0.5 0.2 0.5 0.5 0.4 Television 50.5 55.6 57.4 70.3 59.2 Fridge 7.7 12.0 18.7 24.8 15.9 Mobile phone 82.5 83.5 86.6 86.7 84.7 Electric fan 96.5 96.6 94.0 94.8 95.6 Watch/clock 14.3 19.7 26.5 29.0 22.1 Rickshaw/van 2.3 2.2 3.3 2.4 2.5 Computer/laptop 0.9 1.0 0.7 1.2 1.0 Sewing machine 4.4 4.9 6.9 10.1 6.8

5.4 Household Expenditure and Saving

Table 5.4.1 shows the distribution of households (per cent) by total expenditure during last month. Mean household expenditure was Taka 11,981 during last month. About 60% households spent Taka 10,000-14,999 during last month, followed by Taka 15,000-19,999

41 (15.4%), Taka 7,500-9,999 (13%) and Taka 20,000 or more (6.1%); however, those households spent less than Taka 5,000 were few (1.7%).

Table 5.4.2 shows the distribution of households (per cent) by expenditure on food during last month. Mean household expenditure on food during last month was Taka 6,291. In fact, about 44.4% and households spent Taka 5,000-7,499, followed by Taka 7,500-9,999 (20.3%), Taka 3,000-4,999 (16.3%) and Taka 10,000 or more (11.2%); however those households spent Taka 3,000 or less were few (6.7%).

Table 5.4.1: Distribution of Households (per cent) by Total Expenditure during Last Month

Expenditure Dhalpur & (Taka) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) <5,000 1.2 1.5 1.3 2.5 1.7 5,000-7,499 6.4 5.4 6.3 5.0 5.7 7,500-9,999 14.5 13.6 12.3 11.5 13.0 10,000-14,999 59.1 63.0 59.9 53.1 58.1 15,000-19,999 14.5 11.2 12.8 20.1 15.4 20,000+ 4.3 5.3 7.4 7.8 6.1 Total 100 100 100 100 100 Mean 11,715.3 11,813.1 12,054.8 12,318.7 11,981.5

Table 5.4.3 shows the distribution of households (per cent) by expenditure on health during last month. Mean expenditure on health during last month was Taka 1,276. In fact, 35.2% households did not spend any money on health during last month, 24.9% households spent Taka 1,000 or more, 24.2% households spent Taka 500-999 and 15.7% households spent less than Taka 500.

Table 5.4.4 shows the distribution of households (per cent) by expenditure on education during last month. Mean expenditure on education during last month was Taka 604. In fact, about 60% households did not spend any money on education during last month. Those households spent money on education, 17.6% households spent Taka 1,000 or Taka 500-999, while 6.7% households spent less than Taka 500.

42 Table 5.4.2: Distribution of Households (per cent) by Expenditure on Food during Last Month Expenditure Dhalpur & (Taka) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) <3,000 5.9 5.4 6.0 8.6 6.7 3,000-4,999 15.4 18.8 21.0 13.3 16.3 5,000-7,499 43.4 48.9 42.9 43.0 44.4 7,500-9,999 21.8 16.8 20.4 21.2 20.3 10,000+ 11.4 9.3 9.0 13.2 11.2 Don't know 2.1 0.9 0.6 0.7 1.1 Total 100 100 100 100 100 Mean 6,306.4 6,120.4 6,185.2 6,438.6 6,291.3

Table 5.4.5 shows the distribution of households (per cent) by the amount saved during last month. Mean saving during last month was Taka 527. In fact, majority of the households was unable to save any money (72%), while 12.8% households saved Taka 1,000 or more, followed by 9.1% households saved Taka 500-999 and 5.8% households saved less than Taka 5004.

Table 1Table 5.4.3: Distribution of Households (per cent) by Expenditure on Health during Last Month

Expenditure Dhalpur & (Taka) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) <500 12.5 18.1 12.2 18.8 15.7 500-999 21.8 24.4 25.4 25.8 24.2 1,000+ 20.6 24.0 27.1 28.5 24.9 No expense 45.1 33.4 35.4 26.8 35.2 Total 100 100 100 100 100 Mean 1,078.3 1,191.6 1,640.2 1,357.2 1,275.9

4To know financial condition of the household, an inquiry was made whether any of the household members was a member of NGO/samity and Grameen Bank. In addition, it was also asked whether any household member had taken loan from these NGOs, Grameen Bank, samity, mahajan, relative and others (for detail, see Appendices D.2 and D.3).

It was recorded that 44.2% households had at least one NGO/Grameen/others member. Those who were member, 6.1% in BRAC, 5.5% in ASA, 5.5% in DSK, 1.7% in Grameen, and 1.5% in UPPR, while 23.9% had membership in others category (NGOs/registered or unregistered samity).

About 47% households had taken loan from NGOs, Grameen, mahajan, relative and other sources. Among five NGOs, most of the households had taken loan from BRAC (5.4%), followed by ASA (4.9%), DSK (4.3%), and fewer from UPPR and Grameen (0.3%-1.0%). However, 7.0% households had taken loan from relatives, 2.9% households had taken loan from mahajan, 1.4% households had taken loan from samity, and exceptionally high per cent of loan was taken from other sources (20.3%).

43 Table 5.4.4: Distribution of Households (per cent) by Expenditure on Education during Last Month Expenditure Dhalpur & (Taka) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) <500 6.3 7.2 5.4 7.4 6.7 500-999 16.8 15.6 16.7 20.3 17.6 1,000+ 14.2 13.9 19.3 22.6 17.6 No expense 62.7 63.3 58.6 49.7 58.1 Total 100 100 100 100 100 Mean 485.2 501.1 619.1 781.6 604.2

Table 5.4.5: Distribution of Households (per cent) by Amount Saved during Last Month

Savings Dhalpur & (Taka) Korail Mirpur Shayampur Tongi Total (N=979) (N=667) (N=461) (N=1,006) (N=3,113) <500 2.6 3.9 11.3 7.7 5.8 500-999 14.3 6.5 11.5 4.7 9.1 1,000+ 14.0 12.1 11.9 12.3 12.8 No savings 69.1 77.5 65.3 75.3 72.3 Total 100 100 100 100 100 Mean 518.9 586.8 486.5 514.5 527.2

44 Chapter Six Migration of Household Head Key Findings:

 For 35.7% cases, the household heads migrated 20 years or more ago, while 14% migrated within the last 5 years; 8.6% did not migrate (since birth).  The majority of household heads migrated for work (62.4%), followed by 19.9% migrated for joining family.  50% household heads migrated from Dhaka division, while 20% migrated from Barisal division.

The respondents were asked how long ago (duration) the household heads migrated (from birth place), from which district as well as the cause of migration. The information was collected from all households of the surveillance area.

6.1 Duration of Migration

Table 6.1.1 shows the distribution of migrants (per cent) by duration of migration (household head) and slum locations. For 35.7% household heads migrated 20 or more years ago, followed by 15% migrated during the last 5-9 years, 14.3% migrated within the last 5 years, and 12.6% migrated during the last 10-14 years; 8.6% household heads did not migrate (since birth). Duration of migration did not vary considerably across slum locations, except more migration 20 years ago in Dhalpur/Shayampur (52.9%), followed by Tongi (44.6%), and fewer in Korail and Mirpur (23%-26%). In Tongi, 20.7% household heads did not migrate (since birth), while very few did not migrate in other slums (1%-4%).

45 6.2 Causes of Migration

Table 6.2.2 shows the distribution of migrants (per cent) by cause of migration (household head) and slum locations. The majority of household heads migrated for work (62.4%), followed by joining family (19.9%). Cause of household head’s migration for work varied considerably across slum locations. In Korail, 87.3% household heads migrated for work, followed by Mirpur (65.6%), while comparatively fewer household heads migrated for work in Dhalpur/Shayampur and Tongi (42%-48%). For joining family, most household heads migrated in Dhalpur/Shayampur and Tongi (28%), followed by Mirpur (20.1%), while fewer migrated for joining family in Korail (8.5%).

Table 6.1.1: Distribution of Migrants (per cent) by Duration of Migration+ and Slum Locations Dhalpur & Duration Korail Mirpur Shayampur Tongi Total (Years) (N=9,745) (N=6,230) (N=4,431) (N=10,451) (N=30,857) <5 18.0 21.6 7.9 9.1 14.3 5-9 19.8 21.1 11.0 8.6 15.0 10-14 17.5 14.5 12.1 7.2 12.6 15-19 15.9 13.1 11.5 7.5 11.9 20+ 26.2 23.6 52.9 44.6 35.7 Since birth 1.7 3.7 1.8 20.7 8.6 Missing 0.9 2.4 2.8 2.3 1.9 Total 100 100 100 100 100 Note: +Household head

Table 6.2.1: Distribution of Migrants (per cent) by Cause of Migration+ and Slum Locations Dhalpur & Cause Korail Mirpur Shayampur Tongi Total (N=9,745) (N=6,230) (N=4,431) (N=10,451) (N=30,857) Looking for work 87.3 65.6 48.5 42.3 62.4 Earn more money 0.6 5.2 8.3 2.4 3.2 River erosion 1.6 6.4 1.9 6.4 4.2 To Join family 8.5 20.1 27.4 27.6 19.9 Children’s education 0.0 0.2 0.1 0.1 0.1 Own education 0.1 0.3 0.3 0.3 0.2 Other 0.1 0.7 2.1 0.9 0.8 Since birth 1.8 1.5 11.4 20.0 9.2 Total 100 100 100 100 100 Note: + Household head

46 6.3 Origin of Migration

Table 6.3.1 shows the distribution of migrants (per cent) by origin of migration (household head) and slum locations. 52.2% household heads migrated from Dhaka division, followed by Barisal division (20.5%), Chittagong division (11.6%) and the rest from Khulna, Rajshahi, Rangpur, and Sylhet divisions (15.7%). Origin of household head’s migration varied across slum locations. In Tongi, 71.1% household heads migrated from Dhaka division, while in Mirpur 27.2% household heads migrated from Dhaka division. In Mirpur, 39% household heads migrated from Barisal division, followed by Dhalpur/Shayampur (29.7%), while in Tongi, 9.4% household heads migrated from Barisal division. In Mirpur, 20.5% household heads migrated from Rangpur, while fewer migrated from Rangpur in other slums (3%-6%).

Table 6.3.1: Distribution of Migrants (per cent) by Origin of Migration+ and Slum Locations Dhalpur & Origin Korail Mirpur Shayampur Tongi Total (N=9,745) (N=6,230) (N=4,431) (N=10,451) (N=30,857) Barisal 16.4 39.0 29.7 9.4 20.5 Chittagong 16.7 1.6 16.0 10.9 11.6 Dhaka 54.1 27.2 38.6 71.1 52.2 Khulna 2.3 4.1 3.2 1.1 2.4 Rajshahi 3.5 4.8 2.3 2.1 3.1 Rangpur 4.6 20.5 5.7 3.8 7.7 Sylhet 2.3 2.7 3.5 0.9 2.1 Missing 0.1 0.1 1.0 0.7 0.4 Total 100 100 100 100 100 Note: +Household head

47 Chapter Seven

Challenges to Establish HDSS in Slums

Key Findings: The challenges to establish HDSS were selection of slums, defining study area, taking GIS coordinate of the house, numbering - bari and household, absentee respondent, respondent busy, security of interviewer/Tab, problem related to migration and threat to abolish slum.

For establishing Health and Demographic Surveillance System, the team faced some challenges as below: a) Selection of slums, b) Defining the study area, c) GIS coordinate of the house, d) Numbering - bari and house, e) Absentee respondent - locked household, f) Respondent busy, g) Security of interviewer/Tab, h) Problems related to migration, and i) Threat to abolish slum.

7.1 Challenges

The following challenges were faced while establishing the Health and Demographic Surveillance System in the slums of Dhaka North, Dhaka South and Gazipur City Corporations:

 Selection of slums  Defining the study area  GIS coordinate of the house  Numbering - bari and house  Absentee respondent - locked household  Respondent busy  Security of Field Worker/Tab  Problems related to migration  Threat to abolish slum

7.1.1 Selection of Slums

There are about 4,700 slums in Dhaka North, Dhaka South and Gazipur City Corporations. Out of these slums, some are small (less than 100 households - 93% slums), and some are big (100 or more households - 7% slums); however, about 50% population live in big slums. From the management point of view, big slums are better than small slums (travel time, security etc.) for establishing the HDSS; it was a challenge to select the slums for the HDSS work.

48 7.1.2 Defining the Study Area

Defining the study area was needed to establish the HDSS. The photograph below gives an idea how difficult it was to define the study area for each Field Worker (big slum).

Fig 7.1.2.1: View of Korail Slum in Dhaka

7.1.3 GIS Coordinate of House

As households were very close to each other and sometimes there were two storied houses, it was difficult to take GIS coordinate (time consuming).

Fig 7.1.3.1: Space in between Two Houses

49 7.1.4 Numbering- Bari and Household

It was not very easy to give identification number to the households as the houses were built haphazardly. These household identification numbers were used during the surveillance data collection (three months cycle) and will be used during data collection for special module.

Fig 7.1.4.1: Finding the House

7.1.5 Absentee Respondent - Locked House

The house can be found locked while Field Workers visited. During household listing, some basic information was collected from the neighbour, if the house was found locked. During the baseline population and socioeconomic census, re-visit was needed, if the respondent was not found at home. Asking the neighbour, time was noted for re-visit (early in the morning, lunch break, in the evening, or during the weekend).

50 Fig 7.1.5.1: Locked Household and Note for Availability

7.1.6 Respondent Busy

Often the respondents were found busy and Field Workers had to request the respondent for giving time for interview or time for re-visit.

Fig 7.1.6.1: Respondent Busy

51 7.1.7 Security of Field Worker/Tab5

Slums are not always safe. Sometimes, inconsistent behaviour of drug user, ask for kind/ cash, sex worker in slum; all these put security of the Field Workers and Tab at risk.

Fig 7.1.7.1: Security Issue

7.1.8 Problems Related to Migration During the HDSS data collection, the following difficulties related to migrations/internal movements were faced:

 Internal movement (from which area - to find already assigned Registered Identification Number. Confused with internal movement - moved to which area)  Marriage (one partner, internal or in-migration)  Divorce (divorced woman’s location, internal/out-migration)  Migration-in and migration-out

7.1.9 Threat to Abolish Slum Often slums are destroyed, if they are in government land (illegal settlement), near road side/footpath, and rail line. For private land, slums are often abolished in case of need for constructing better houses.

5 In this study, an enquiry was also made whether any of the household members was affected by violence, robbery, theft, kidnapping, and sexual harassment during the last six months (for detail, see Appendix D.4).

About 20% households were affected by such incidences during the last six months. Among five incidences, most prevalent was the theft and least was kidnapping. In fact, about 10% households suffered from theft during the last six months, 5% households suffered from violence, 1.7% households suffered from sexual harassment, 1.2% households suffered from robbery and 0.7% households suffered from kidnapping.

52 7.2 Strategies to Overcome Challenge  Strong supervision  Field office for meeting  Work beyond office hour  Rapport building (household member)  Community support (local leader)  Utilization of the image of icddr,b

53 References

Ahmed, SMA, Islam K, Bhuiya A. 2015. Urban Health Scenario: Looking Beyond 2015. Dhaka: Bangladesh Health Watch.

BBS, 2015. Census of Slum Areas and Floating Population - 2014, Bangladesh Bureau of Statistics, Statistics Division, Ministry of Planning, Government of the People's Republic of Bangladesh.

Bangladesh Urban Health Survey 2013- Preliminary Results, National Institute of Population Research and Training, MEASURE Evaluation, UNC-Chapel Hill, USA, and icddr,b.

Bangladesh Urban Health Survey 2006, Dhaka, Bangladesh and Chapel Hill, NC, USA: NIPORT, MEASURE Evaluation, icddr,b and ACPR; 2008, http://www.cpc.unc.edu/measure

Chowdhury, A M R, Abbas Bhuiya, Mahbub Elahi Chowdhury, Sabrina Rasheed, Zakir Hussain, Lincoln C Chen, The Bangladesh Paradox: Exceptional Health Achievement despite Economic Poverty, Lancet 2013; 382: 1734–45, November 21, 2013, http://dx.doi.org/10.1016/S0140-6736(13)62148-0

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United Nations Population Division. 2003. World Urbanization Prospects: The 2003 Revision, New York, United Nations.

United Nations Population Division. World Urbanization Prospects: The 2014 Revision, New York, United Nations.

54 Appendix A: Key Findings- Baseline Population and Socioeconomic Census, 2015-16 Results of baseline population and Results from other Indicators socioeconomic census-Dhaka North, slum surveys Dhaka South and Gazipur City Corportations, 2015-2016 Population by broad age groups (%) 0-14 yrs. 31.4 33.2+ 15-64 yrs. 66.0 66.4+ 65 or more yrs. 2.6 2.4+ Family size 3.8 4.1+ Female headed household (%) 17.6 14.2++ Sex ratio 97.8 104.8+ Dependency ratio (%) Total 51.6 - Young 47.7 57++ Old 3.9 - No education Among aged 15 or more yrs. (%) Male 36.2 25.7+ (aged 15-54) Female 42.3 31.8+ (aged 15-49) Among aged 6-14 yrs. (%) Boy 14.1 - Girl 8.9 - Occupation Income generating activity (%) Male 73.5 - Female 39.6 38.1+ Laborer (%) Male 26.4 - Female 4.6 - Garment worker (%) Male 10.3 - Female 19.1 - Student (%) Male 14.5 - Female 14.7 - Ownership (%) Mobile phone 84.7 92.0+ Television 59.2 63.0+ Electric fan 95.6 93.0+ Expenditure/saving during last month (Taka) Total household expenditure Mean 11,981 - Taka 10,000-14,999 (%) 58.1 - Household expenditure on food Mean 6291 - Taka 5,000-9,999 (%) 64.7 - Household expenditure on health Mean 1,276 - Taka 1,000 or more (%) 24.9 -

55 Household expenditure on education Mean 604 - Taka 1,000 or more (%) 17.6 - Household saving Mean 52.7 - Taka 1,000 or more (%) 12.8 - Ownership of land (%) Owned by government 90.7 7.9+ Ownership of house (%) Tenant 67.8 75.6+ Owned by HH/other member 31.6 21.2+ Dwelling (%) One bed room 81.6 74.6+ Mean area of dwelling sq. ft. 119.4 Construction material of dwelling (%) Roof- Tin 94.0 88.4+ Wall- Tin 70.4 42.6+ Floor- Brick/cement 88.0 75.4+ Source of drinking water (%) Pipe water 93.8 59.3+ Sharing water source- 10 or more HH 37.4 64.7+ Type of toilet (%) Sanitary flash to sewerage/tank 29.5 1.0+ Sanitary flash to elsewhere 60.9 8.6+ Ventilated improved pit 0.5 82.8+ Sharing toilet- 10 or more HH 31.7 42.9+ Source of light (%) Electricity 99.6 97.8+ Type of fuel for cooking (%) Gas line 53.5 Wood 34.9 Sharing cooking place-10 or more HHs 15.9 Garbage disposal system (%) Type of store (%) Open space outside 47.3 47.4+ At home/bin outside 47.2 52.3+ Frequency of collection (%) Every day 41.8 Never collected 36.5 Migration of household head Duration of migration (%) Less than 5 yrs. 14.3 Twenty or more yrs. 35.7 Since birth 8.6 Cause of migration (%) Looking for work 62.4 To join family 19.9 Origin of migration (%) Dhaka 52.2 Barisal 20.5 Chittagong 11.6 Note: +Bangladesh Urban Health Survey, 2013; ++Bangladesh Urban Health Survey, 2006.

56 Appendix B: Member of Technical Review Committee

1. Md. Abu Bakr Siddique, Project Director (Joint Secretary), UPHCSDP 2. Mr. Dhiraj Kumar Nath, Staff consultant, BRM, ADB 3. Dr. Zahirul Islam, Program Officer, Embassy of Sweden, Dhaka 4. Dr. Rafiqus Sultan, PTO, UNFPA 5. Director (Research), NIPORT 6. Prof. Nitai Chakraborty, Department of Statistics, University of Dhaka 7. Dr. Md. Shafiqul Islam, Associate Professor, Department of Epidemiology, NIPSOM 8. Chief Health Officer, Dhaka South City Corporation 9. Chief Health Officer, Dhaka North City Corporation 10. Dr. Abdur Razzaque, PhD, PI, Operations Research, (icddr,b) 11. Mr. Sabirul Islam, Deputy Project Director, (A&T/SD), UPHCSDP

57 Appendix C.1: Distribution of Slums by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014

Slum Size Locality Total % of < 10 HH 10-24 HH 25-49 HH 50-99 HH 100+ HH slums slums 1 2 3 4 5 6 7 Barisal 14 45 34 23 20 136 0.98

Chittagong 313 1002 348 335 217 2215 15.89

Comilla 9 9 12 5 5 40 0.29

Dhaka (N) 255 769 264 157 199 1644 11.80

Dhaka (S) 527 851 254 85 38 1755 12.59

Gazipur 192 616 257 143 78 1286 9.23

Narayanganj 5 18 15 17 27 81 0.58

Khulna 630 361 62 47 34 1134 8.14

Rajshahi 13 24 16 19 31 103 0.74

Rangpur 0 4 7 17 20 48 0.34

Sylhet 217 339 75 35 4 670 4.81

City Corp Total 2175 4038 1344 883 672 9112 65.38

Municipalities 1082 1089 480 409 290 3350 24.04

Other Urban 485 700 186 77 28 1476 10.59

Grand Total 3742 5827 2010 1369 990 13938 100.00 Source: BBS, 2015; HH=Household

58 Appendix C.2: Distribution of Households by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014

Slum Size % of Locality Total HHs < 10 HH 10-24 HH 25-49 HH 50-99 HH 100+ HH HHs 1 2 3 4 5 6 7 Barisal 107 746 1157 1658 5897 9565 1.61

Chittagong 2199 15755 12043 23164 74275 127436 21.49

Comilla 63 125 377 341 849 1755 0.30

Dhaka (N) 1732 12100 9062 10940 101227 135061 22.78

Dhaka (S) 3574 13112 8843 5612 8874 40015 6.75

Gazipur 1423 9309 8928 10180 26757 56597 9.54

Narayanganj 43 308 594 1292 8567 10804 1.82

Khulna 3909 5078 2119 3376 6054 20536 3.46

Rajshahi 65 425 582 1415 7727 10214 1.72

Rangpur 0 72 287 1280 4415 6054 1.02

Sylhet 1444 4925 2519 2301 702 11891 2.01

City Corp Total 14559 61955 46511 61559 245344 429928 72.50

Municipalities 7160 16159 16916 29128 60438 129801 21.89

Other Urban 3273 10247 6177 5421 8151 33269 5.61

Grand Total 24992 88361 69604 96108 313933 592998 100.00 Source: BBS, 2015; Note: HH=Household

59 Appendix C.3: Distribution of Population by Slum Size and Locality (City Corporation, Municipality and Other Urban), 2014

Slum Size % of Locality Total < 10 HH 10–24 HH 25–49 HH 50-99 HH 100+ HH popu- popn lation 1 2 3 4 5 6 7 Barisal 420 3027 4810 6671 23808 38738 1.74

Chittagong 7970 58626 44833 90995 282406 484830 21.76

Comilla 257 556 1614 1331 3688 7446 0.33

Dhaka (N) 6305 42842 31965 39684 375873 496669 22.29

Dhaka (S) 12969 47989 32037 21224 32847 147066 6.60

Gazipur 4689 28547 27507 32827 92297 185867 8.34

Narayanganj 165 1178 2202 4976 31964 40485 1.82

Khulna 14628 19242 8610 13612 23735 79827 3.58

Rajshahi 226 1479 2263 5209 29364 38541 1.73

Rangpur 0 255 1032 4521 16156 21964 0.99

Sylhet 6049 20714 10665 9733 2968 50129 2.25

City Corp Total 53678 224455 167538 230783 915106 1591560 71.44

Municipalities 27513 63120 66613 114827 241540 513613 23.06

Other Urban 12162 37581 22895 20714 29229 122581 5.50

Grand Total 93353 325156 257046 366324 1185875 2227754 100.00 Source: BBS, 2015; Note: HH=Household

60 Appendix D.1: Under-Five Care (per cent) when Mothers Work Outside

100 90.2 90

80

70

60

50

40

30

20

10 3.7 4.3 0.8 0.3 0.2 0.5 0 No body Siblings neighbour Relatives Daycare Others NA

Appendix D.2: Loan Received (per cent) from NGO/Others

25

20.3 20

15

10 7.0 5.4 4.9 5 4.3 2.9 1.0 1.4 0.3 0 DSK UPPR BRAC Grameen ASA Samity Mohajan Relative Others

61 Appendix D.3: NGO/Samity Membership

30

25 23.9

20

15

10 5.5 6.1 5.5 5 1.5 1.7

0 DSK UPPR BRAC Grameen ASA Others

Appendix D.4: Members Affected by Violence, Robbery etc. During the Last Six Months

12

9.8 10

8

6 4.7

4

1.5 2 1.2 0.6

0 Theft Crime/Violence Sexual Robbery Kidnap harassment

62 Appendix E.1: Baseline Population and Socioeconomic Census, 2015-16 (All HH) Urban Health and Demographic Surveillance System, icddr,b

1. Sl. No.___ 2. Name of slum: ______Code: ____ 3. Name of bariwala: ______Bari No: ___ 4. Household No:______5. Religion: ____ 6. Nameofhouseholdhead:______7.HowlongHHlivinginthislocation1:____ 8.HowlongagoHHleftpermanentaddress:___ 9. Upazila: ______10. Division: ______11. Reason for leaving permanent address2 (HH): ______12 13 14 15 16 17 18 19 20 21 22 23 Occupation Desire for child (married woman age Ind. Mother's Date of Marital status4 Relation to Education RID Name Age Sex3 (age 8+)7 12-49) No. No. birth (age 12+) head5 (age 5+) (Primary) Years of Desire for child: If yes, when do Type6 schooling Yes=1, No=2, you want next (completed) Pregnant=3, DK=4 pregnancy (yr.) 01 02 03 04 05 06 07 08 09 10 11

1How long household (year) living in this location (Korail Basti, Molla Basti, Bhola Basti, Dwaripara Basti, Nishat Nagar Basti, Kalabagan Basti, Bank Field Basti, Hazi Mazar Basti, Ershad Nagar Basti, Dhalpur Basti (Pura, Driver, Nubur, City Palli, Power House, and Mannan Basti), Shayampur Basti (Dhaka Mach Colony, Dhaka Mach Rail line Basti, Namapara Basti), NA (since birth= 99). 2Reason for leaving permanent address (household head): Looking for work=1, To earn more money=2, River erosion=3, To join family=4, For children's education=5, For own education=6, Other=7, NA (since birth) =9. 3Sex: Male=1, Female=2, Transgender=3. 4Marital status: Currently married=1, Separated=2, Divorced=3, Widowed=4, Never married=5. 5Relation to head: No relation=0, Self=1, Husband=2, Son=3, Brother=4, Son-in-law= 5, Father=6, Father-in-Law=7, Grandson=8, Wife=9, Daughter=10, Sister=11, Daughter-in-law=12, Mother=13, Mother-in-law=14, Granddaughter=15, Others=99. 6Education type: No schooling=0, Secular (govt.) =1, Secular (private) =2, Secular (NGO) =3, Religion=4. 7Occupation: Private service=1, Garment worker=2, Govt. service =3, Self-employed=4, Rickshaw/van puller=5, Business=6, Laborer (skill & un-skill)=7, Housewife=8, Domestic work(female)=9, Domestic work (male) =10, Student=11, No work=12, Others=13.

63 Socioeconomic Information 24 Who own the land of dwelling? Head/other resident=1 Landlord=2 Government=3 Other=4 25 Who own the dwelling? Head/other resident=1 House owner/Bariwala=2 Other=4 26 Do you have the following items in your house? Chair/table=1 Dining table=2 Khat=3 Chowki=4 Almirah/wardrobe=5 Sofa set=6 Radio=7 Television=8 Fridge=9 Mobile phone=10 Electric fan=11 Watch/clock=12 Rickshaw/van=13 Computer/laptop=14 Sewing machine=15 Respondent’s individual No.:___ Respondent/Household’s mobile No.:______Interviewer’s name and code:______Note: Appendix E.2: Baseline Socioeconomic Census, 2015-16 (Sample HH) Urban Health and Demographic Surveillance System, icddr,b No. Questionnaire Category 1 Date: __/___/___ 2 Name of slum: _____ Code: ______3 Household No 4 Name of household head: ______5 Name of bariwala: ______6 Bari No: ______7 Respondent’s name: ______8 Ind. No: ______9 What material roof of main dwelling is made? Polythene/thatch=1 Wood/bamboo=2 Tin=3 Brick/cement=4 10 What material from which wall of main dwelling is Polythene/thatch=1 made? Wood/bamboo=2 Tin=3 Brick/cement=4 11 What material floor of main dwelling is made? Earth(Katcha)=1 Wood/bamboo=2 Brick/cement=3 12 Number of dwelling (room)? No:__ 13 Area of dwelling (sq. ft.)- (1st room) Length:___ 14 Area of dwelling (sq. ft.)- (1st room) Breadth:___ 15 Area of dwelling (sq. ft.)-(2nd room) Length:___ 16 Area of dwelling (sq. ft.)-(2nd room) Breadth:___ 17 Area of dwelling (sq. ft.)-(3rd room) Length:___ 18 Area of dwelling (sq. ft.)-(3rd room) Breadth:___ 19 Area of dwelling (sq. ft.)-(4rd room) Length:___ 20 Area of dwelling (sq. ft.)-(4rd room) Breadth:___ 21 What is the main source of drinking water for your Pipe water=1 household? Tube well=2 Well=3 Others=4 22 Is drinking water source inside dwelling/yard/plot? Yes=1 No=2 23 Any other families share main drinking water source? Yes=1 No=2 24 If yes, how many families share drinking water source? No.___ 25 What kind of toilet facility does your household use? Sanitary- flash to sewerage/septic tank=1 Sanitary- flash to somewhere=2 Ventilated improved pit=3 Pit latrine without slab=4 Hanging latrine/open=5 No facility=6 26 Is toilet facility inside dwelling/yard/plot? Yes=1 No=2 27 Any other families share the latrine? Yes=1 No=2

65 No. Questionnaire Category 28 If yes, how many families share the latrine? No.___ 29 Source of light? Electricity=1 Kerosene oil=2 Generator=3 Solar panel=4 Others=5 29 What type of fuel does your household use for Gas-line=1 cooking? Gas-cylinder=2 Wood=3 Kerosene=4 Electricity=5 Others=6 30 Is cooking place inside the dwelling? Yes=1 No=2 31 Any other families share the cooking place? Yes=1 No=2 30 If yes, how many families share cooking place? No.___ 31 Principal method for garbage disposal? Collected from home (inside)=1 Bin outside house=2 Open space outside=3 Others=4 32 How frequently garbage is collected from the place Every day=1 where you dispose it? 1-3 times a week=2 3-4 time a month=3 Never collect=4 33 a. Have you or someone in the household been victim Yes=1 of violence in the last 6 months? No=2 b. Have you or someone in the household been victim Yes=1 of street robbery in the last 6 months? No=2

c. Have you or someone in the household been victim Yes=1 of theft in the last 6 months? No=2

d. Have you or someone in the household been victim Yes=1 of abduction/kidnapping in the last 6 months? No=2 e. Have you or someone in the household been victim Yes=1 of sexual harassment in the last 6 months? No=2 34 How much did you spend last month for your family Total(all):___ (Taka)? How much did you spend last month for your family House rent___ (Taka)? Electricity___ Gas______Water______Dish______Food______Health_____ Education__ Mobile____ 35 Household savings (surplus) last month? Taka____ 36 Do you (respondent) have voter ID? Yes=1 No=2

66 No. Questionnaire Category 37 Do you (respond) know where the ward Yes=1 commissioner's office? No=2 38 If the household had under-five chid, who takes care Nobody=1 him/her while mother works outside? Siblings=2 Neighbour=3 Relative=4 Day-care=5 Others=6 NA=7 39 Age of care giver (siblings, neighbour, relative, others) Year:___ 40 Is anybody in the household, member of NGO/samity? Yes=1 No=2 41 If yes, name of NGO/samity? DSK=1 UPPR=2 brac3 Grameen=4 ASA=5 Other=6 Did anybody in the household has taken loan from Yes=1 DSK, UPPR, brac, Grameen, ASA, Samity, Mahajan, No=2 Relative, Others. If yes, name? DSK=1 UPPR=2 brac=3 Grameen=4 ASA=5 Mohajan=6 Relative=7 Others=8 If yes, how much loan? Tk.___ How much loan is unpaid? Tk.___ Individual number of loan receiver? No.___

67