Poverty and Groundwater Salinity Survey 2016
Bangladesh, 2016
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Reference ID
BGD_2016_PGSS_v01_M
DOI
https://doi.org/10.48529/wp20-rf54
Producer(s)
Monica Yanez-Pagans
Metadata
Created on
Aug 21, 2017
Last modified
Aug 21, 2017
Page views
27092
Downloads
34209
Identification
Survey ID Number
BGD_2016_PGSS_v01_M
Title
Poverty and Groundwater Salinity Survey 2016
Country/Economy
| Name | Country code |
|---|---|
| Bangladesh | BGD |
Study type
Other Household Survey [hh/oth]
Abstract
The main objective of the Bangladesh Poverty and Groundwater Salinity Survey (BPGSS) 2016 is to understand the linkages between groundwater salinity and poverty in coastal areas in Bangladesh. It is also to assess the extent to which high water salinity might be associated with poor health outcomes among women and children, and identify potential coping and adaptation mechanisms, which households might be using to address high water salinity in these areas.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household
Scope
Notes
The scope of the survey includes the following:
- Household: Household characteristics, employment, assets, land, livestock, utilities, remittances, water and sanitation, farming
- Household members: age, sex, education, hypertension, pregnancy complications
- Migration: reasonss for migration
- Household: Household characteristics, employment, assets, land, livestock, utilities, remittances, water and sanitation, farming
- Household members: age, sex, education, hypertension, pregnancy complications
- Migration: reasonss for migration
Coverage
Geographic Coverage
The three upazilas selected for this study are the following: (i) Taltoli upazila in the Barguna district of the Barisal division; (ii) Morrelganj upazila in the Bagerhat district of the Khulna division; and (iii) Shyamnagar upazila in the Satkhira district in the Khulna division
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Monica Yanez-Pagans | World Bank |
Sampling
Sampling Procedure
The Bangladesh Poverty and Groundwater Salinity Survey 2016 collected data from a total of 1,500 households in three sub-districts or upazilas in Bangladesh – 500 households in each upazila distributed across 50 primary sampling units (PSUs). The three upazilas selected for this study are the following: (i) Taltoli upazila in the Barguna district of the Barisal division; (ii) Morrelganj upazila in the Bagerhat district of the Khulna division; and (iii) Shyamnagar upazila in the Satkhira district in the Khulna division. Each upazila was allocated an equal size of households in order to get poverty estimates of similar precision. The sampling frame consists of a list of all rural villages developed by the Bangladesh Bureau of Statistics (BBS) based on the Census Enumeration Areas (CEAs) constructed for the 2011 Census of Population and Housing. PSUs are constructed by dividing rural villages into listing blocks or Enumeration Areas (EAs) of around 50 households each and then randomly selecting one block for listing.
The three upazilas included in this study where selected based on discussion with a water salinity expert in Bangladesh and practical considerations using a two-stage procedure. In the first stage, we combined upazila level poverty data from the official 2010 Bangladesh Poverty Maps with upazila level information on groundwater salinity collected by the Bangladesh Water Development Board (BWDB) with support from the Institute of Water Modelling (IWM). Using these combined dataset, we classified all 146 upazilas in coastal areas in four groups: (i) high water salinity and high poverty rate; (ii) high water salinity and low poverty rates; (iii) low water salinity and high poverty rate; (iv) low water salinity and low poverty rates. Figure 1 shows the spatial distribution of coastal area upazilas based on these four categories. In the second stage, we selected one upazila from each of the first three categories as focal areas for this study after discussion with a groundwater expert on availability of other water-supply options (e.g. managed aquifer recharge) and practical considerations. This categorization of upazilas also serve as our three sampling strata – high water salinity and high poverty rate, high water salinity and low poverty rates, and low water salinity and high poverty rate.
The three upazilas included in this study where selected based on discussion with a water salinity expert in Bangladesh and practical considerations using a two-stage procedure. In the first stage, we combined upazila level poverty data from the official 2010 Bangladesh Poverty Maps with upazila level information on groundwater salinity collected by the Bangladesh Water Development Board (BWDB) with support from the Institute of Water Modelling (IWM). Using these combined dataset, we classified all 146 upazilas in coastal areas in four groups: (i) high water salinity and high poverty rate; (ii) high water salinity and low poverty rates; (iii) low water salinity and high poverty rate; (iv) low water salinity and low poverty rates. Figure 1 shows the spatial distribution of coastal area upazilas based on these four categories. In the second stage, we selected one upazila from each of the first three categories as focal areas for this study after discussion with a groundwater expert on availability of other water-supply options (e.g. managed aquifer recharge) and practical considerations. This categorization of upazilas also serve as our three sampling strata – high water salinity and high poverty rate, high water salinity and low poverty rates, and low water salinity and high poverty rate.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2016 | 2016 |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name |
|---|
| Nielsen Company |
Questionnaires
Questionnaires
The household questionnaire is available in Bengali and English under the Related Materials tab.
Data Processing
Data Editing
Data entry and editing was done by Survey CTO.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Monica Yanez-Pagans | World Bank | myanezpagans@worldbank.org | |
| Yurani Arias-Granada | World Bank | yariasgranada@worldbank.org | |
| Microdata Library | World Bank | microdata.worldbank.org |
Confidentiality
Before being granted access to the dataset, all users have to formally agree:
1. To make no copies of any files or portions of files to which s/he is granted access except those authorized by the data depositor.
2. Not to use any technique in an attempt to learn the identity of any person, establishment, or sampling unit not identified on public use data files.
3. To hold in strictest confidence the identification of any establishment or individual that may be inadvertently revealed in any documents or discussion, or analysis. Such inadvertent identification revealed in her/his analysis will be immediately brought to the attention of the data depositor.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
The World Bank. Bangladesh Poverty and Groundwater Salinity Survey (BPGSS) 2016. Ref. BGD_2016_PGSS_v01_M. Downloaded from [URL] on [Date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Example:
The World Bank. Bangladesh Poverty and Groundwater Salinity Survey (BPGSS) 2016. Ref. BGD_2016_PGSS_v01_M. Downloaded from [URL] on [Date].
Access authority
| Name | Affiliation | URL |
|---|---|---|
| Microdata Library | World Bank | microdata.worldbank.org |
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Metadata production
DDI Document ID
DDI_BGD_2016_PGSS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2017-08-17
DDI Document version
Version 01 (August 2017)