WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Baseline and Endline Surveys 2009-2011
Indonesia, 2008 - 2010
Water and Sanitation Program
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Identification
Survey ID Number
IDN_2009-2011_WSP-IE_v01_M_v01_A_PUF
Title
WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Baseline and Endline Surveys 2009-2011
Country
| Name | Country code |
|---|---|
| Indonesia | IDN |
Study type
Other Household Health Survey [hh/hea]
Series Information
The IE includes several rounds of household and community surveys: pre-intervention (baseline), concurrent (longitudinal), and post-intervention (endline). The surveys are designed to collect information on the characteristics of the eligible population and to track changes in desired outcomes.
Abstract
In response to the preventable threats posed by poor sanitation and hygiene, in December 2006 the Water and Sanitation Program (WSP) launched two related large-scale projects, Global Scaling Up Handwashing1 and Global Scaling Up Rural Sanitation. Th ese hygiene and sanitation interventions are designed to improve the health and welfare outcomes for millions of poor people. Local and national governments are implementing these projects with technical support from WSP.
The goal of Global Scaling Up Rural Sanitation is to reduce the risk of diarrhea and therefore increase household productivity by stimulating demand for sanitation in the lives of people in India, Indonesia, and Tanzania. Th e project approach demands involvement from communities, local government, and the private sector. It aims to trigger the desire for an open-defecation free community by raising collective awareness of the open defecation problem. Facilitators are sent to communities to initiate participatory analysis of the communities’ existing sanitation practices, and the consequences and implications of such practices for themselves. Th is process is designed to catalyze collective community desire and action to become open defecation free (ODF). Th e community must forge their own plan for making this happen with only limited follow-up support and monitoring from the program. Communities claiming to have become ODF are verifi ed by local government agencies. ODF achievement by a community brings recognition and commendation from local and provincial governments. Th e project also seeks to stimulate the supply of appropriate sanitation products and services by conducting market research and training local artisans to build the relevant facilities.
To measure the magnitudes of the impacts, the project is implementing randomized-controlled trial impact evaluations (IE) study in order to establish causal linkages between the intervention (treatment) and the outcomes of interest. Th e IE uses household surveys to measure the levels of key outcomes.
The overall objective of the project is to improve the health of populations at risk of diarrhea, especially in children under the age of five years, through highlighting the negative health consequences of poor sanitation. Th e impact evaluation provides a unique opportunity to learn what health and welfare impacts can be expected from sanitation improvements. If, as expected, the evaluation finds strong health and child development impacts of improved sanitation, the study will be an important promotional tool for expanding the program across the nation. But to generate the support needed for a national program, the evidence must be clear and compelling. It is therefore important that the impact evaluation use widely accepted impact evaluation protocols and that it disrupts the planned program as little as possible.
The impact evaluation assesses the effects of the project on individual-level sanitation behaviors, community-level collective behaviors, and the program’s impact on the health and welfare of young children (under fi ve years of age). It examines the impact on a broad range of health indicators and intensively studies the developmental, social, and economic welfare impacts of these interventions. Health outcomes that are explicitly planned in the study include:
• Diarrhea prevalence;
• Stunting and wasting;
• Iron defi ciency anemia (through minimally invasive fi nger-prick tests);
• Parasitic infestations (from fecal samples); and
• Cognitive and motor development.
Some of the non-health indicators are:
• School attendance, academic performance, and future earnings;
• Productivity of mother’s time for household, market, and social activities; and
• Female empowerment and security due to safer sanitation conditions.
(The above excerpt is taken from: Scaling Up Rural Sanitation: Findings from the Impact Evaluation Baseline Survey in Indonesia by Lisa Cameron and Manisha Shah November 2010)
The report is attached.
The goal of Global Scaling Up Rural Sanitation is to reduce the risk of diarrhea and therefore increase household productivity by stimulating demand for sanitation in the lives of people in India, Indonesia, and Tanzania. Th e project approach demands involvement from communities, local government, and the private sector. It aims to trigger the desire for an open-defecation free community by raising collective awareness of the open defecation problem. Facilitators are sent to communities to initiate participatory analysis of the communities’ existing sanitation practices, and the consequences and implications of such practices for themselves. Th is process is designed to catalyze collective community desire and action to become open defecation free (ODF). Th e community must forge their own plan for making this happen with only limited follow-up support and monitoring from the program. Communities claiming to have become ODF are verifi ed by local government agencies. ODF achievement by a community brings recognition and commendation from local and provincial governments. Th e project also seeks to stimulate the supply of appropriate sanitation products and services by conducting market research and training local artisans to build the relevant facilities.
To measure the magnitudes of the impacts, the project is implementing randomized-controlled trial impact evaluations (IE) study in order to establish causal linkages between the intervention (treatment) and the outcomes of interest. Th e IE uses household surveys to measure the levels of key outcomes.
The overall objective of the project is to improve the health of populations at risk of diarrhea, especially in children under the age of five years, through highlighting the negative health consequences of poor sanitation. Th e impact evaluation provides a unique opportunity to learn what health and welfare impacts can be expected from sanitation improvements. If, as expected, the evaluation finds strong health and child development impacts of improved sanitation, the study will be an important promotional tool for expanding the program across the nation. But to generate the support needed for a national program, the evidence must be clear and compelling. It is therefore important that the impact evaluation use widely accepted impact evaluation protocols and that it disrupts the planned program as little as possible.
The impact evaluation assesses the effects of the project on individual-level sanitation behaviors, community-level collective behaviors, and the program’s impact on the health and welfare of young children (under fi ve years of age). It examines the impact on a broad range of health indicators and intensively studies the developmental, social, and economic welfare impacts of these interventions. Health outcomes that are explicitly planned in the study include:
• Diarrhea prevalence;
• Stunting and wasting;
• Iron defi ciency anemia (through minimally invasive fi nger-prick tests);
• Parasitic infestations (from fecal samples); and
• Cognitive and motor development.
Some of the non-health indicators are:
• School attendance, academic performance, and future earnings;
• Productivity of mother’s time for household, market, and social activities; and
• Female empowerment and security due to safer sanitation conditions.
(The above excerpt is taken from: Scaling Up Rural Sanitation: Findings from the Impact Evaluation Baseline Survey in Indonesia by Lisa Cameron and Manisha Shah November 2010)
The report is attached.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household
Person
Caregiver
Child (under 5 and under 2)
Person
Caregiver
Child (under 5 and under 2)
Version
Version Description
Version 1.1: The study includes information on the baseline, longitudunal and endline surveys.
Version 1.2: Treatment data file (TSSMTreatmentControlList.dta) uploaded 5/3/2016
Version 1.2: Treatment data file (TSSMTreatmentControlList.dta) uploaded 5/3/2016
Version Date
2012-01-31
Scope
Notes
The survey covered the following topics:
- Geographic Identification/Location and Administrative/Supervision Information
- Household Roster
- Education
- Labor
o Labor Force Participation
o Primary Work
o Additional Work
- Household Income
- Assets
- Dwelling Characteristics
- Observation of Food Storage
- Observation of Drinking Water
- Observation of Handwashing Facility
- Observation of Latrine/ Toilet
- Observation of Animals and Feces
- Water Source
- Sanitation Facility
- Observations of Children
- Perception of Illness
- Caregiver Time Use
- Child Health Calendar
- Breastfeeding
- Infant/ Young Child Feeding
- Mortality
- Anthropometry and Anemia
- Geographic Identification/Location and Administrative/Supervision Information
- Household Roster
- Education
- Labor
o Labor Force Participation
o Primary Work
o Additional Work
- Household Income
- Assets
- Dwelling Characteristics
- Observation of Food Storage
- Observation of Drinking Water
- Observation of Handwashing Facility
- Observation of Latrine/ Toilet
- Observation of Animals and Feces
- Water Source
- Sanitation Facility
- Observations of Children
- Perception of Illness
- Caregiver Time Use
- Child Health Calendar
- Breastfeeding
- Infant/ Young Child Feeding
- Mortality
- Anthropometry and Anemia
Topics
| Topic | Vocabulary |
|---|---|
| Impact Evaluation | World Bank |
| Health | World Bank |
Coverage
Geographic Coverage
The surveys convered eight districts.
Geographic Unit
The survey was undertaken in the commune (clusters). But as this is an impact evaluation, this is not a nationally representative statistic.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Water and Sanitation Program | World Bank |
Producers
| Name | Role |
|---|---|
| Kimetrica International | Data reduction endline |
Funding Agency/Sponsor
| Name | Role |
|---|---|
| Bill & Melinda Gates Foundation | Primary funding source for the impact evaluation |
Sampling
Sampling Procedure
The project is being implemented in 29 rural districts (kabupaten) in East Java. Eight of those 29 districts are participants in the impact evaluation-a total of 2080 households in 160 sub-villages (dusun). The sample is geographically representative and representative of the households in rural East Java.
A total of 160 sub-villages from eight districts are participants in the IE. From each district, 10 treatment and 10 control villages were randomly chosen to participate in the IE. Local government offices from each district gave the IE team a list of at least 30 villages where the program could be implemented. Most district offices gave the IE teams lists of 40-70 villages. These are villages the districts had chosen to participate in the project based on sanitation needs, poverty levels, access to water, and so forth.3 Using a random number generator in STATA, the IE team randomly selected 10 treatment and 10 control villages from each district list. The IE team then sent the list of 20 villages back to the district government office (without telling them which villages had been selected as control and treatment villages). The reason for this is that the project is actually implemented at the dusun, or sub-village level. Villages generally have two to three sub-villages. Wanting the same selection criteria to be used for the selection of sub-village for both the treatment and control villages, the IE team asked each district office to provide the sub-village names for all 20 villages. District offices were told that some would be the treatment and others the control.
Once the IE team received the sub-village lists from the district offices for all 20 villages, the district offices were told which villages were in the treatment group and which ones were in the control group. The district offices committed that they would do everything possible to make sure the treatment dusun were treated and the control dusun remained untreated. There was some concern by local program implementers that the program might spread like "wildfire" and that it would be difficult to deny control villages the program. However, sample sizes were selected based on this possibility and it does not appear that many control villages have been contaminated.
Note: Detail sampling procedure is available in "Scaling Up Rural Sanitation: Findings from the Impact Evaluation Baseline Survey in Indonesia" November 2010 survey report.
A total of 160 sub-villages from eight districts are participants in the IE. From each district, 10 treatment and 10 control villages were randomly chosen to participate in the IE. Local government offices from each district gave the IE team a list of at least 30 villages where the program could be implemented. Most district offices gave the IE teams lists of 40-70 villages. These are villages the districts had chosen to participate in the project based on sanitation needs, poverty levels, access to water, and so forth.3 Using a random number generator in STATA, the IE team randomly selected 10 treatment and 10 control villages from each district list. The IE team then sent the list of 20 villages back to the district government office (without telling them which villages had been selected as control and treatment villages). The reason for this is that the project is actually implemented at the dusun, or sub-village level. Villages generally have two to three sub-villages. Wanting the same selection criteria to be used for the selection of sub-village for both the treatment and control villages, the IE team asked each district office to provide the sub-village names for all 20 villages. District offices were told that some would be the treatment and others the control.
Once the IE team received the sub-village lists from the district offices for all 20 villages, the district offices were told which villages were in the treatment group and which ones were in the control group. The district offices committed that they would do everything possible to make sure the treatment dusun were treated and the control dusun remained untreated. There was some concern by local program implementers that the program might spread like "wildfire" and that it would be difficult to deny control villages the program. However, sample sizes were selected based on this possibility and it does not appear that many control villages have been contaminated.
Note: Detail sampling procedure is available in "Scaling Up Rural Sanitation: Findings from the Impact Evaluation Baseline Survey in Indonesia" November 2010 survey report.
Weighting
Not applicable
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2008-08 | 2008-09 | Baseline survey |
| 2010 | 2010 | Endline survey |
Data Collection Mode
Face-to-face [f2f]
Data Collectors
| Name |
|---|
| Survey Meter |
Questionnaires
Questionnaires
The following instruments were used to collect the data:
• Household questionnaire: The household questionnaire was conducted in all households and was designed to collect data on household membership, education, labor, income, assets, dwelling characteristics,water sources, drinking water, sanitation,observations of handwashing facilities and other dwelling characteristics, handwashing behavior, child discipline, maternal depression, handwashing determinants, exposure to health interventions, relationship between family and school, and mortality.
• Health questionnaire: The health questionnaire was conducted in all households and designed to collect data on children's diarrhea prevalence, ALRI and other health symptoms, child development, child growth, and anemia.
• Community questionnaire: The community questionnaire was conducted in 120 districts to collect data on community/districts variables.
• Structured observations: Structured observations were conducted in a subsample of 160 households to collect data on direct observation of handwashing behavior.
• Water samples: Water samples were collected in a subsample of 160 households, to identify Escherichia coli (E. coli) presence in hand rinses (mother and children), sentinel toy, and drinking water.
• Stool samples: Stool samples were collected in a subsample of 160 households to identify prevalence of parasites in children's feces.
• Household questionnaire: The household questionnaire was conducted in all households and was designed to collect data on household membership, education, labor, income, assets, dwelling characteristics,water sources, drinking water, sanitation,observations of handwashing facilities and other dwelling characteristics, handwashing behavior, child discipline, maternal depression, handwashing determinants, exposure to health interventions, relationship between family and school, and mortality.
• Health questionnaire: The health questionnaire was conducted in all households and designed to collect data on children's diarrhea prevalence, ALRI and other health symptoms, child development, child growth, and anemia.
• Community questionnaire: The community questionnaire was conducted in 120 districts to collect data on community/districts variables.
• Structured observations: Structured observations were conducted in a subsample of 160 households to collect data on direct observation of handwashing behavior.
• Water samples: Water samples were collected in a subsample of 160 households, to identify Escherichia coli (E. coli) presence in hand rinses (mother and children), sentinel toy, and drinking water.
• Stool samples: Stool samples were collected in a subsample of 160 households to identify prevalence of parasites in children's feces.
Data Processing
Other Processing
The data files as they are output in CSPro follow the hierarchical structure as established in the data dictionary. These however may not be convenient for the analyst. The WSP requested that the files be integrated into various record level files. The files that are included in the final data base reflect this structure.
However, some analysts may still want the hierarchical level data available in its original record form (as it was during data entry). For that reason, these files are also zipped together and provided in the event that they are desired.
The final data files are provided in STATA format as requested by the WSP.
However, some analysts may still want the hierarchical level data available in its original record form (as it was during data entry). For that reason, these files are also zipped together and provided in the event that they are desired.
The final data files are provided in STATA format as requested by the WSP.
Data Appraisal
Estimates of Sampling Error
Not applicable
Access policy
Access authority
| Name | Affiliation | |
|---|---|---|
| Bertha Briceno | Water and Sanitation Program | bbriceno@worldbank.org |
| Alex Orsola-Vida | Water and Sanitation Program | aorsolavidal@worldbank.org |
Contacts
| Name | Affiliation | |
|---|---|---|
| Claire Chase | WSP | cchase@worldbank.org |
| Bertha Briceno | WSP | bbriceno@worldbank.org |
Access conditions
Access authority is defined in a policy document entitled: WSP Data Access Policy. This document is attached. However, the following is provided from the data access policy:
To access data, team members must complete a Data Access Request Form (attached). Although team members may already have physical access to a particular dataset, they are expected to complete a Data Access Request Form (attached) if they intend to conduct a new analysis and/or prepare a new abstract, conference presentation, or manuscript.
All Data Access Request Forms should be submitted to Bertha Briceno (bbriceno@worldbank.org). In the event that Bertha is unavailable, the data access request form should be submitted to Alex Orsola-Vidal (aorsolavidal@worldbank.org).
Once the data access request form is submitted and approved, Bertha or Alex will facilitate the team member's access to the necessary data. WSP will strive to centralize storage of the latest datasets for analysis by all team members. Until WSP centralizes data storage, the individual Country PIs will be able to distribute the latest datasets for their respective countries.
The responsible team member must ensure that data are not distributed to anyone other than researchers listed on the Data Access Request Form.
The following team members will have access to data upon request and approval of the Data Access Request Form (attached).
• Country PIs
• Global experts
• WSP team
• Students or trainees of country PIs, global experts, or WSP team members will have access to data only after the supervising PI, global expert, or WSP team member complies with the process described here, including submitting the student's signed request for data access and agreement to comply with authorship and publication guidelines described. It is the supervising team member's responsibility to ensure that the student comply with all guidelines contained within this document.
To access data, team members must complete a Data Access Request Form (attached). Although team members may already have physical access to a particular dataset, they are expected to complete a Data Access Request Form (attached) if they intend to conduct a new analysis and/or prepare a new abstract, conference presentation, or manuscript.
All Data Access Request Forms should be submitted to Bertha Briceno (bbriceno@worldbank.org). In the event that Bertha is unavailable, the data access request form should be submitted to Alex Orsola-Vidal (aorsolavidal@worldbank.org).
Once the data access request form is submitted and approved, Bertha or Alex will facilitate the team member's access to the necessary data. WSP will strive to centralize storage of the latest datasets for analysis by all team members. Until WSP centralizes data storage, the individual Country PIs will be able to distribute the latest datasets for their respective countries.
The responsible team member must ensure that data are not distributed to anyone other than researchers listed on the Data Access Request Form.
The following team members will have access to data upon request and approval of the Data Access Request Form (attached).
• Country PIs
• Global experts
• WSP team
• Students or trainees of country PIs, global experts, or WSP team members will have access to data only after the supervising PI, global expert, or WSP team member complies with the process described here, including submitting the student's signed request for data access and agreement to comply with authorship and publication guidelines described. It is the supervising team member's responsibility to ensure that the student comply with all guidelines contained within this document.
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
World Bank Water and Sanitation Program. Indonesia WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Baseline and Endline Surveys 2009-2011. Ref. IDN_2009_2011_WSP-IE_v01_M_v01_A_PUF. Dataset downloaded from [website/source] 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
World Bank Water and Sanitation Program. Indonesia WSP Global Scaling Up Rural Sanitation Access (TSSM) Impact Evaluation, Baseline and Endline Surveys 2009-2011. Ref. IDN_2009_2011_WSP-IE_v01_M_v01_A_PUF. Dataset downloaded from [website/source] on [date]
Disclaimer and copyrights
Disclaimer
WSP is a multi-donor partnership created in 1978 and administered by the World Bank to support poor people in obtaining affordable, safe, and sustainable access to water and sanitation services. WSP's donors include Australia, Austria, Canada, Denmark, Finland, France, the Bill & Melinda Gates Foundation, Ireland, Luxembourg, Netherlands, Norway, Sweden, Switzerland, United Kingdom, United States, and the World Bank. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the Water and Sanitation Program, the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Metadata production
DDI Document ID
DDI_IDN_2009-2011_WSP-IE_v01_M_v01_A_PUF
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kimetrica International | Kimetrica | Compiled the DDI | |
| Water and Sanitation Project | WSP | World Bank | Reviewed content of the DDI |
Date of Metadata Production
2012-01-31
DDI Document version
Version 1.1: Adopted from "DDI-WSP-INDO-IE2009-2011" DDI that was done by metadata producers mentioned in "Metadata Production" section.
Version 1.2 (May 2016): Treatment data file (TSSMTreatmentControlList) uploaded on 5/3/2016
Version 1.2 (May 2016): Treatment data file (TSSMTreatmentControlList) uploaded on 5/3/2016