{"doc_desc":{"title":"zaf-acc-hcp-cpt-2013-2017-v1","producers":[{"name":"DataFirst","abbr":"","affiliation":"University of Cape Town","role":"Metadata producer"}],"prod_date":"2024-08-23","version_statement":{"version":"v2"}},"study_desc":{"title_statement":{"idno":"zaf-acc-hcp-cpt-2013-2017-v1","title":"Hungry Cities Partnership Survey","sub_title":"Cape Town 2013-2017","alternate_title":"HCP 2013-2017"},"authoring_entity":[{"name":"Hungry Cities Partnership, African Centre for Cities","affiliation":"University of Cape Town"}],"production_statement":{"funding_agencies":[{"name":"International Development Research Centre","abbr":"IDRC","role":"Funder"},{"name":"Social Sciences and Humanities Research Council","abbr":"SSHRC","role":"Funder"}]},"distribution_statement":{"contact":[{"name":"DataFirst Support","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"www.support.data1st.org"}]},"series_statement":{"series_name":"Household Survey [hh]","series_info":"Hungry Cities Partnership, African Centre for Cities, University of Cape Town. Hungry Cities Partnership Survey 2013-2017, Cape Town. [dataset]. Version 1. Cape Town: HCP [producer], 2020. Cape Town: DataFirst [distributor], 2020. DOI: https:\/\/doi.org\/10.25828\/9pn8-5b51"},"version_statement":{"version":"V1: Cleaned and anonymised for public use","version_date":"2020-11-06"},"study_info":{"abstract":"This study covers Cape Town, one of four African cities surved between 2013 and 2019 by the African Center for Cities. The African Center for cities is based at the University of Cape Town and is a partner of the Hungry Cities Partnership (HCP).\n\nThe HCP studies include household data on food insecurity, household food purchasing dynamics, nutritional discounting taking place in households, foods consumed and multidimensional measures of poverty. The household data is complimented with household member data and food retailer (vendor) data, including infomation on vendor employees.\n\nThe Hungry Cities Partnership is an international network of cities and city-based partner organizations which focuses on the relationships between rapid urbanization, informality, inclusive growth and urban food systems in the Global South.","coll_dates":[{"start":"2013","end":"2017","cycle":"Both surveys"},{"start":"2017","end":"2017","cycle":"Vendor survey"},{"start":"2013","end":"2013","cycle":"Household survey"}],"nation":[{"name":"South Africa","abbreviation":"zaf"}],"geog_coverage":"The household sample is deisgned to be representative of the city of Cape Town.","geog_unit":"In the public release the lowest geographic level is the city (Cape Town). In the secure version of the data, the lowest geographic\/administrative unit at which dissagregated data is available is the Enumeration Area. GPS data is also available in the secure version.","analysis_unit":"Households and individuals","universe":"Households and Vendors in Cape Town.","data_kind":"Sample survey data","notes":"The houeshold surveys adopted the USAID-aligned Food and Nutrition Technical Assistance modules, detailed by the measures of the Household Food Insecurity Access Scale, Household Food Insecurity Access Prevalence Scale, Household Dietary Diversity Score and the Months of Adequate Food Provisioning. The surveys provide data on food insecurity, household food purchasing dynamics, nutritional discounting taking place in households, and foods consumed. Over and above this, the surveys also provide insights into the levels of multidimension poverty, through the use of the Lived Poverty Index. This combination highlights the connections between food insecurity and lived poverty. \n\nThe informal vendor survey instrument sought information on issues including vendor demographic characteristics, entrepreneurial motivations, business financing, enterprise character, operations, challenges, strategies, and aspirations of the vendors."},"method":{"data_collection":{"data_collectors":[{"name":"Citizen Surveys","abbr":"","role":"","affiliation":""},{"name":"","abbr":"","role":"","affiliation":""}],"sampling_procedure":"Household sampling: the sample for the 2013 Food Security Study was designed to be two-stage and stratified, using a random probability sample of 2,500 Cape Town households .Enumeration areas were taken from Statistics SAs master lists and used as the primary sampling unit. Households were the secondard sampling unit. Strafitication was done by income group of the household. Some areas were over-sampled to improve accuracy. In each of the drawn EAs, six households were systematically selected, with the exception of the EAs in DuNoon (where 10 households were systematically selected). Starting points were allocated to ensure coverage of the entire EA. The household was defined by everyone who regularly \"ate from the same pot\". \n\nVendor sampling: The survey team documentation reads as follows: A strategy of maximum variation sampling was used to ensure a mix of commercial, formal residential, informal residential, mixed formal and informal residential, and industrial retail sites. In these areas, the main street served as the primary site of research. Informal food vending businesses were selected randomly. In total, 1,018 food vendors were interviewed over a three-week period. \n\nFor more on sampling see the study documentation.","sampling_deviation":"In cases, xenophobic violence made vendor interviews dangerous in some areas.","coll_mode":["Face-to-face [f2f]"],"research_instrument":"There are two questionnaires per city, a household questionnaire and a vendor questionnaire. The household questionnaire has a subsection for household members (persons), and the vendor quesitonnaire has a subsection for employees. Answers to these subsections are supplied in separete datafiles, which can be matched to (merged with) the questoinnaire as necessary. \n\nVendor surveys were administered to the person directly responsible for the running of the business using handheld tablets. The household survey was administered to a senior adult member of the household, someone who could speak for the household. \n\nNote that for the household questionnaire, the question 8 section changed slightly for Cape Town, in that the answers are not stored in 'wide' format like the other cities. Rather, if a respondent provided more than one answer, additional variables were created. This is why the dataset has less variables and the question 8 section looks different. Only up to three locations were recorded in section 8, even if the repondent mentioned more than 3 sources of food.","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"The household data was collected in 2013, the vendor data in 2017.","act_min":"This project received ethics approval by the Ethics in Research Commitee of the Faculty of Commerce at the University of Cape Town on the 13th of April 2015.","weight":"Household: Design weights were calculated based on the survey design. These were them adjusted post-hoc to account for non-random patterns of non-repsonse. The adjustment was done using 2015 mid-year estimates as the auxiliary data, and nthe CALMAR method. See the technical documents for more information.\n\nThe vendor data is not weighted, although the collection team says it \"tried to take a representative sample\".","cleaning_operations":"Datafiles were received by DataFirst in SPSS (.sav) and Excel (.xlsx) format. Variables had to be named and variable labels were taken from question text. Variables were named accoriding to question number and subject matter, in a hierachical fasion. \n\nAn effort was made to keep question numbers consistent across cities where the same questions were asked for the 2013-2019 surveys. For the vendor data, Cape Town, Maputo and Nairobi had almost identical questionnaires and so the question numbers were naturally the same across these cities (harmonized). For the household data, Maputo, Nairobi and Windhoek were similar and could be harmonized. This means users could try stack these datafiles. The Cape Town household questionnaire was more different to the others, and variable names would required adjusting to match with the other cities. \n\nMissing values of 97, 98, and 99 were converted to -97, -98 and -99. There were some question numbers wrong in the vendor data questionnaires (typos) that were corrected."},"analysis_info":{"data_appraisal":"It seems that there is slight mismatch between the Cape Town household questionnaire provided and the lists in the datafile, for an example see the question 15 income sources. \n\nIn the Cape Town household data, data was not collected for the quetion 10.c and 10.d, about crops and time to travel to crops. \n\nIn general, the lists change subtly between cities, for example the lists of foods in question 8 of the household data. As such the user should take caution when comparing across cities, and refer to the questionnaires. When the lists differed, list item letters (a-z) were left in the variable name as a second way for the user to check that the data match the questionnaire in the expected way. In Cape Town an answer to questions 15a and b \"support from relatives\" was captured although it does not reflect in the questionnaire."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"support.data1st.org"}],"cit_req":"Hungry Cities Partnership & African Centre for Cities. Hungry Cities Partnership Survey, Cape Town 2013-2017. [dataset]. Version 1. Cape Town: HCP [producer], 2020. Cape Town: DataFirst [distributor], 2020. DOI: https:\/\/doi.org\/10.25828\/9pn8-5b51","conditions":"Public use files, available to all"}}},"schematype":"survey"}