Comprehensive Food Security and Vulnerability Analysis Assessment 2008
Ghana, 2008
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Identification
Survey ID number
GHA_2008_CFSVA_v01_M
Title
Comprehensive Food Security and Vulnerability Analysis Assessment 2008
Country
| Name | Country code |
|---|---|
| Ghana | GHA |
Study type
Comprehensive Food Security & Vulnerability Analysis [hh/cfsva]
Series Information
The CFSVA process generates a document that describes the food security status of various segments of a population over various parts of a country or region, analyses the underlying causes of vulnerability, and recommends appropriate interventions to deal with the problems. CFSVAs are undertaken in all crisis-prone food-insecure countries. The shelf life of CFSVAs is determined by the indicators being collected and reported. In most situations, CFSVA findings are valid for three to five years, unless there are drastic food security changes in the meantime.
Abstract
The primary aim of the Comprehensive Food Security and Vulnerability Analysis (CFSVA) in Ghana is to provide much needed baseline information on the food security, health and nutrition situation in the entire country at sub-national and agro-ecological level in both, rural and urban areas.
This baseline study is meant to inform and guide WFP's and its partners' programming - most importantly that of the newly inaugurated government - mandated to address food insecurity and its underlying causes. It is meant to serve as a tool with a potential to refine the implementations of GPRS II, the UNDAF and similar future development frameworks that aim to achieve the Millennium Development Goals (MDG). The survey provides reliable, comprehensive and multi-sectoral information that should assist in strengthening targeting, identifying priority areas for interventions, etc.
Specifically, the CFSVA is intended to:
· Assess levels of household food insecurity in ten administrative regions, three agroecological zones and in urban and rural areas while focusing on the following questions:
· Who are the food insecure people?
· Where do they live?
· Why are they food insecure?
· How and what type of external assistance play a role in improving the food insecurity situation?
· Identify the main livelihoods in the country and analyse their contribution to food security at regional, agro-ecological, rural and urban level, and analyse households' capacity to withstand future shocks and problems;
· Assess households and communities' dependence on markets and the impact increasing food prices have had and are expected to have on their lives and livelihoods;
· Assess the prevalence and distribution of malnutrition among children and mothers and define the relationship between food insecurity and malnutrition by determining whether the underlying reasons for prevailing child malnutrition are consumption or health related;
· Determine which populations or regions of the country are most vulnerable to poor health outcomes;
· Identify key indicators to be captured in the already operational Food Security Monitoring System to detect changes and trends in food security and vulnerability situation over time.
This baseline study is meant to inform and guide WFP's and its partners' programming - most importantly that of the newly inaugurated government - mandated to address food insecurity and its underlying causes. It is meant to serve as a tool with a potential to refine the implementations of GPRS II, the UNDAF and similar future development frameworks that aim to achieve the Millennium Development Goals (MDG). The survey provides reliable, comprehensive and multi-sectoral information that should assist in strengthening targeting, identifying priority areas for interventions, etc.
Specifically, the CFSVA is intended to:
· Assess levels of household food insecurity in ten administrative regions, three agroecological zones and in urban and rural areas while focusing on the following questions:
· Who are the food insecure people?
· Where do they live?
· Why are they food insecure?
· How and what type of external assistance play a role in improving the food insecurity situation?
· Identify the main livelihoods in the country and analyse their contribution to food security at regional, agro-ecological, rural and urban level, and analyse households' capacity to withstand future shocks and problems;
· Assess households and communities' dependence on markets and the impact increasing food prices have had and are expected to have on their lives and livelihoods;
· Assess the prevalence and distribution of malnutrition among children and mothers and define the relationship between food insecurity and malnutrition by determining whether the underlying reasons for prevailing child malnutrition are consumption or health related;
· Determine which populations or regions of the country are most vulnerable to poor health outcomes;
· Identify key indicators to be captured in the already operational Food Security Monitoring System to detect changes and trends in food security and vulnerability situation over time.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Surveys were conducted at the community and household level for analysis at sub-national and agro-ecological level in both, rural and urban areas.
Version
Version Date
2009-05-31
Scope
Notes
The scope of the analysis includes:
HOUSEHOLD: Demographics, education, migration, housing, facilities, assets, agriculture, access to markets, income sources, access to credit, expenditure, food consumption, food sources, shocks, risks, coping, assistance
WOMEN (from the household questionnaire): Pregnancy status, healthcare status, height, weight
CHILDREN under 5 (from the household questionnaire): Health status, height, weight, birth information, breastfeeding information, food consumption
COMMUNITY: Village demographics, socioeconomic information, infrastructure, migration, food security, health programs, healthcare access, water access, education, external assistance, shocks, emergency preparedness
Coverage
Geographic Coverage
National coverage
Universe
The sample universe for this study was all residents of the household
A household is defined as a group of people currently eating from the same pot "under the same roof" (or in same compound if the household has more than one structure).
A household is defined as a group of people currently eating from the same pot "under the same roof" (or in same compound if the household has more than one structure).
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| World Food Programme | United Nations |
Producers
| Name | Role |
|---|---|
| World Health Organization | Technical assistance |
| Ghana Statistical Service | Knowledge support |
| Ghana Ministry of Food and Agriculture | Knowledge support |
| Ghana Ministry of Economic and Social Welfare | Knowledge support |
| Ghana Ministry of Health/Nutrition Unit | Knowledge support |
Funding Agency/Sponsor
| Name | Role |
|---|---|
| Bill and Melinda Gates Foundation | Financial support |
| Department for International Development | Financial support |
| World Health Organization | Financial support |
Sampling
Sampling Procedure
The CFSVA sampling strategy aimed at providing sufficiently precise estimates of several key food security indicators for all rural regions, as well as Urban Accra, and all other urban areas together in one domain.
As a CFSVA aims to provide estimates of many different indicators, no single indicator can guide sample size requirements. Therefore, when calculating minimal sample size, an assumed prevalence of 50% was used, this yields the largest sample sized for a required precision. A design effect of 2 was assumed (food security indicators typically used in similar CFSVAs usually have design effects ranging from near 1 to 4). 95% confidence is always used, with intervals of +/- 8%. Following the standard sample size calculation for estimating prevalences, this yields a sample of approximately 260 households per domain. Where possible, larger samples were taken to increase precision.
Due to the time and cost limitations of drawing a new accurate sample, it was decided to 'piggy-back' on the existing sample already drawn for the on-going DHS survey. The DHS sample is a 2-stage cluster sample, with the following sample distribution:
Ghana DHS 2008 cluster numbers by region (urban and rural)
Region Urban Rural Total
Western 15 24 39
Central 13 21 34
Gt. Accra 53 7 60
Volta 10 25 35
Eastern 16 27 43
Ashanti 36 31 67
Brong Ahafo 16 22 38
Northern 11 27 38
Upper East 5 23 28
Upper West 7 23 30
Total 182 230 412
The clusters used throughout the country are 'Enumeration Areas', or EAs. At the time of the CFSVA, Ghana Statistical Services had already recently drawn up this sample, complete with household listings for each selected EA (cluster). Rather than draw a new sample, a sub-sample of this was taken for the CFSVA. In this sub-sample, all rural clusters selected for the DHS were maintained in the CFSVA sample, and a sub-set of urban clusters were randomly selected from the DHS sample in each of the regions for inclusion in the CFSVA (thus maintaining the PPS selection of clusters). This resulted in a non-self-weighting sample, so probability weights were used in analysis to account for this.
Once the clusters were selected this way, it was decided to select 12 households per cluster to allow for sufficient total sample size per domain, while allowing for enumerator teams (consisting of 1 team leader and 4 enumerators) to complete, on average, one cluster per day. This also yielded at least 260 households per strata (or just under, and with the exception of rural Accra). As GSS has previously conducted a complete listing for all EAs in the DHS, they were able to randomly select 12 households per cluster (with 3 additional replacement households if one or more of the 12 were unavailable). The enumerator teams were supplied with maps of the EAs and the locations of the households and the names of the household heads.
This resulted in the final sample, by domain:
Domain Clusters Households (planned) Households (actually sampled) Number of these that were replacement households
Western Rural 24 288 288 38
Central Rural 21 252 252 37
Gt. Accra Rural 7 84 84 19
Volta rural 25 300 299 56
Eastern rural 27 324 324 55
Ashanti rural 31 372 372 59
Brong Ahafo rural 22 264 264 38
Northern rural 27 324 324 43
Upper East rural 23 276 276 27
Upper West rural 23 276 276 17
Urban Accra 42 504 504 129
Urban Other 49 588 588 103
Total 321 3852 3851 621
It should be noted here that Rural Accra has well below the goal of 260 households for that strata. Due to the very small rural population in that Region, and the fact that the DHS only had 7 rural clusters selected, it was decided that a sample yielding very low precision would be acceptable for that region.
In each cluster, an attempt to give the households an advance notice was made wherever possible, particularly in urban areas. Additionally, enumerators were instructed to make multiple re-visits (within the same day of visit to the EA) in order to try to capture the selected households. However, as can be noted from the table above, there was a high number of replacement households (overall, 16% of the sample) particularly in urban areas (21% of urban households and 14% of rural households). This could result in some bias if the absent/unreachable households were different than the randomly selected replacements.
Additional geographic reporting strata included urban/rural, and ecological zone. A probability weights were used in the analysis to compensate for the unequal selection probabilities throughout the country, the sample was representative for any geographic division, and the sample size allowed for sufficient precision within these alternative stratifications.
For nutrition indicators of children under 5, it was determined that the sample size would be too low to yield sufficiently precise estimates. Therefore, it was decided to aggregate the nutrition estimates at the zonal level and urban/rural for the majority of the analyses. In all households selected, all children under 5 were selected to be weighted and measured, as well as all women between 15 to 49 years old (pregnant women were not weighed and measured). Further discussion of the nutrition sample is presented in the nutrition data annex. For the community questionnaire, one questionnaire was administered in each EA (cluster).
As a CFSVA aims to provide estimates of many different indicators, no single indicator can guide sample size requirements. Therefore, when calculating minimal sample size, an assumed prevalence of 50% was used, this yields the largest sample sized for a required precision. A design effect of 2 was assumed (food security indicators typically used in similar CFSVAs usually have design effects ranging from near 1 to 4). 95% confidence is always used, with intervals of +/- 8%. Following the standard sample size calculation for estimating prevalences, this yields a sample of approximately 260 households per domain. Where possible, larger samples were taken to increase precision.
Due to the time and cost limitations of drawing a new accurate sample, it was decided to 'piggy-back' on the existing sample already drawn for the on-going DHS survey. The DHS sample is a 2-stage cluster sample, with the following sample distribution:
Ghana DHS 2008 cluster numbers by region (urban and rural)
Region Urban Rural Total
Western 15 24 39
Central 13 21 34
Gt. Accra 53 7 60
Volta 10 25 35
Eastern 16 27 43
Ashanti 36 31 67
Brong Ahafo 16 22 38
Northern 11 27 38
Upper East 5 23 28
Upper West 7 23 30
Total 182 230 412
The clusters used throughout the country are 'Enumeration Areas', or EAs. At the time of the CFSVA, Ghana Statistical Services had already recently drawn up this sample, complete with household listings for each selected EA (cluster). Rather than draw a new sample, a sub-sample of this was taken for the CFSVA. In this sub-sample, all rural clusters selected for the DHS were maintained in the CFSVA sample, and a sub-set of urban clusters were randomly selected from the DHS sample in each of the regions for inclusion in the CFSVA (thus maintaining the PPS selection of clusters). This resulted in a non-self-weighting sample, so probability weights were used in analysis to account for this.
Once the clusters were selected this way, it was decided to select 12 households per cluster to allow for sufficient total sample size per domain, while allowing for enumerator teams (consisting of 1 team leader and 4 enumerators) to complete, on average, one cluster per day. This also yielded at least 260 households per strata (or just under, and with the exception of rural Accra). As GSS has previously conducted a complete listing for all EAs in the DHS, they were able to randomly select 12 households per cluster (with 3 additional replacement households if one or more of the 12 were unavailable). The enumerator teams were supplied with maps of the EAs and the locations of the households and the names of the household heads.
This resulted in the final sample, by domain:
Domain Clusters Households (planned) Households (actually sampled) Number of these that were replacement households
Western Rural 24 288 288 38
Central Rural 21 252 252 37
Gt. Accra Rural 7 84 84 19
Volta rural 25 300 299 56
Eastern rural 27 324 324 55
Ashanti rural 31 372 372 59
Brong Ahafo rural 22 264 264 38
Northern rural 27 324 324 43
Upper East rural 23 276 276 27
Upper West rural 23 276 276 17
Urban Accra 42 504 504 129
Urban Other 49 588 588 103
Total 321 3852 3851 621
It should be noted here that Rural Accra has well below the goal of 260 households for that strata. Due to the very small rural population in that Region, and the fact that the DHS only had 7 rural clusters selected, it was decided that a sample yielding very low precision would be acceptable for that region.
In each cluster, an attempt to give the households an advance notice was made wherever possible, particularly in urban areas. Additionally, enumerators were instructed to make multiple re-visits (within the same day of visit to the EA) in order to try to capture the selected households. However, as can be noted from the table above, there was a high number of replacement households (overall, 16% of the sample) particularly in urban areas (21% of urban households and 14% of rural households). This could result in some bias if the absent/unreachable households were different than the randomly selected replacements.
Additional geographic reporting strata included urban/rural, and ecological zone. A probability weights were used in the analysis to compensate for the unequal selection probabilities throughout the country, the sample was representative for any geographic division, and the sample size allowed for sufficient precision within these alternative stratifications.
For nutrition indicators of children under 5, it was determined that the sample size would be too low to yield sufficiently precise estimates. Therefore, it was decided to aggregate the nutrition estimates at the zonal level and urban/rural for the majority of the analyses. In all households selected, all children under 5 were selected to be weighted and measured, as well as all women between 15 to 49 years old (pregnant women were not weighed and measured). Further discussion of the nutrition sample is presented in the nutrition data annex. For the community questionnaire, one questionnaire was administered in each EA (cluster).
Weighting
Probability weights were used in analysis to compensate for unequal selection probabilities. At the household level, these weights were based on the 2000 census population data. For the child and mother data, specific weights were calculated based on the 2000 census data for these populations. All analysis is weighted unless otherwise specified. All reported sample sizes are unweighted.
Survey instrument
Questionnaires
The questionnaires had been pilot tested prior to the training and were pilot tested again by each of the enumerators as part of the training. WHO was particularly involved in the design and analysis of the health and nutrition related aspects of the survey.
01 - Household Questionnaire - The household questionnaire was designed to collect quantitative data in 10 areas: (1) demographics and education, (2) migration information, (3) housing, facilities, and assets, (4) agriculture and access to market, (5) income sources and access to credit, (6) expenditure, (7) food consumption and sources, (8) shocks, risks and coping, (9) assistance, and (10) woman and child health and nutrition
02 - Community Questionnaire - The community questionnaire was structured, open ended and designed to collect qualitative information on (1) demographics, (2) socioeconomic information and infrastructure, (3) working population migration, (4) food security, (5) health, (6) education, (7) external assitance, (8) past event / shock identification, and (9) emergency preparedness. The community questionnaire was intended to contextualize the information collected at the household level. The resulting instrument was a structured, open-ended questionnaire. Response options were not systematically provided to the enumerators. Rather, the enumerators were asked to record exactly what respondents had to say.
01 - Household Questionnaire - The household questionnaire was designed to collect quantitative data in 10 areas: (1) demographics and education, (2) migration information, (3) housing, facilities, and assets, (4) agriculture and access to market, (5) income sources and access to credit, (6) expenditure, (7) food consumption and sources, (8) shocks, risks and coping, (9) assistance, and (10) woman and child health and nutrition
02 - Community Questionnaire - The community questionnaire was structured, open ended and designed to collect qualitative information on (1) demographics, (2) socioeconomic information and infrastructure, (3) working population migration, (4) food security, (5) health, (6) education, (7) external assitance, (8) past event / shock identification, and (9) emergency preparedness. The community questionnaire was intended to contextualize the information collected at the household level. The resulting instrument was a structured, open-ended questionnaire. Response options were not systematically provided to the enumerators. Rather, the enumerators were asked to record exactly what respondents had to say.
Data collection
Dates of Data Collection
| Start | End |
|---|---|
| 2008-10-30 | 2008-12-01 |
Data Collectors
| Name |
|---|
| Ghana Statistical Service |
Supervision
World Food Programme
Data Collection Notes
An eight-day training for enumerators took place from 20 to 28 October 2008 during which eighty-three enumerators were trained in the administration of the data collection tools and measurement of anthropometrics. The questionnaires had been pilot tested prior to the training and were pilot tested again by each of the enumerators as part of the training. Seventy-five trainees were selected for the data collection exercise, based on best performance during the pilot, participation in the class-room training and the result of a one-hour written test.
Fifteen teams were created each of which consisted of one team leader and four enumerators. In each Enumeration Area one community interview was carried out with a maximum of ten and minimum of three randomly selected key informants (i.e. chief, village nurse, extension officer, traditional healers, teachers, etc.) and twelve questionnaires were administered with heads of randomly, pre-selected selected households.
By the end of the data collection exercise, 321 communities and 3,851 households had been interviewed. Anthropometric measurements (weights, heights) were taken from 2,231 children between 0-59 months and of 4,069 women between 15 to 49 years (reproductive age).
Fifteen teams were created each of which consisted of one team leader and four enumerators. In each Enumeration Area one community interview was carried out with a maximum of ten and minimum of three randomly selected key informants (i.e. chief, village nurse, extension officer, traditional healers, teachers, etc.) and twelve questionnaires were administered with heads of randomly, pre-selected selected households.
By the end of the data collection exercise, 321 communities and 3,851 households had been interviewed. Anthropometric measurements (weights, heights) were taken from 2,231 children between 0-59 months and of 4,069 women between 15 to 49 years (reproductive age).
Data processing
Data Editing
The data entry masque (CSPRO) for both, the household and community questionnaire, were developed by the GSS and reviewed by the WFP RB and WHO. Data entry started one week before the completion of the data collection. GSS data entry clerks double entered every household and community questionnaire. Qualitative data from the community questionnaire were directly inputted into the database which was then shared with WHO for coding. Data entry took 30 days. The GSS carried out some preliminary data cleaning, transferred the data into SPSS and shared the database with WFP RB for analysis.
access_policy
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 acronym and year of implementation)
- the survey reference number
- the source and date of download
- the Identification of the Primary Investigator
- the title of the survey (including acronym and year of implementation)
- the survey reference number
- the source and date of download
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.
Copyright
© World Food Programme, Vulnerability Analysis and Mapping Branch (VAM)
Metadata production
DDI Document ID
DDI_GHA_2008_CFSVA_v01_M
Producers
| Name | Affiliation | Role |
|---|---|---|
| Amit Wadhwa | WFP | Data Archivist |
| World Bank Development Data Group | World Bank |
Date of Metadata Production
2009-08-26
Metadata version
DDI Document version
Version 1.1 (26 August 2009)
Study ID edited for internal use at the World Bank (3 February 2014)
Study ID edited for internal use at the World Bank (3 February 2014)