Gauteng City-Region Observatory Quality of Life Survey 2011
Other Household Survey [hh/oth]
The Gauteng-City Region Observatory (GCRO) commissioned Data World to conduct its Second Quality of Life Survey, with surveys being conducted in second half of 2011.
The Gauteng City-Region Observatory (GCRO) was established in 2008 as a partnership between the University of Johannesburg (UJ), the University of the Witwatersrand, Johannesburg (Wits) and the Gauteng Provincial Government (GPG), with local government in Gauteng also represented. The objective of the GCRO is to inform and assist the various spheres of the Gauteng government in building and maintaining the province as an integrated and globally competitive region.
The Second Quality of Life Survey must comprehensively represent the whole of Gauteng, which consists of 10 municipalities, which in turn covers 508 wards. Data World was contracted to undertake 15000 surveys across this sphere. Among the main aims of the Quality of Life Survey, is to inform the GCRO as well as provincial government and other relevant parties with regards to the perceived states of the municipalities within Gauteng, with focus on the quality of the lives of people who live within these municipalities.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The units of analysis in theGauteng City-Region Observatory (GCRO) Quality of Life Survey are households and individuals
v1: Edited, anonymised dataset available for use in DataFirst's research data centre.
The Gauteng City-Region Observatory Quality of Life Survey 2011 collected data on demographic details of the enumerated population (population group, gender, age, language) and on housing (dwelling type, tenure, satisfaction with dwelling, perceived quality of housing and housing allocation) as well as household services (water, sanitation, refuse, energy sources). Data was also collected on migration, health (including disability), education and employment (including employment sector). Data on community services and amenities was also collected, and on transport, leisure activities and safety and crime. Financial data was collected (including on debts, income, and social grants) and data on household assets. Data on public participation and governance was also collected during the survey. Finally, the survey collected data on the perceived personal wellbeing and quality of life of respondents.
economic conditions and indicators [1.2]
income, property and investment/saving [1.5]
domestic political issues [4.2]
government, political systems and organisations [4.4]
basic skills education [6.1]
compulsory and pre-school education [6.2]
vocational education [6.7]
general health [8.4]
health care and medical treatment [8.5]
specific diseases and medical conditions [8.9]
TRANSPORT, TRAVEL AND MOBILITY 
family life and marriage [12.5]
community, urban and rural life [13.1]
cultural activities and participation [13.2]
social conditions and indicators [13.8]
specific social services: use and provision [15.3]
The Gauteng City-Region Observatory Quality of Life Survey 2011 covers the whole of Gauteng and also areas with GCR 'footprints' in the four neighbouring provinces of Free State, North West, Limpopo and Mpumalanga.
The lowest level of geographic aggregation in the Gauteng City-Region Observatory Quality of Life Survey 2009 is municipality
The Gauteng City-Region Observatory Quality of Life Survey 2009 covered all household residents of Gauteng and selected areas of the four neighbouring provinces of Free State, North West, Limpopo and Mpumalanga.
Producers and sponsors
Gauteng City-Region Observatory
University of Johannesburg
Gauteng Provincial Government
For the purpose of this study, multi-stage cluster sampling was used as no sampling frame containing all members in the universe or population exists. The sample was drawn in stages, with wards being selected at the first stage, dwelling
units within the wards being selected in the second stage and respondents selected at the third stage.
The wards formed the primary sampling units (PSUs). A random starting point(s) was used as a method to select the dwelling units to be surveyed. A total number of 602 wards in 4 provinces (Gauteng 448 wards), (Mpumalanga 72 wards), (North-West 70 wards) and (Free State 12 wards) were completed. A total of 6639 interviews were completed in these wards.
During the second phase, the field teams were required to complete a certain number of interviews, depending on the population size of that particular ward. The teams had to complete for an example in ward X 3 interviews and in ward Y they had to complete 33 interviews. This meant that the field teams had different target number of interviews that they needed to complete in all the pre-selected wards. Ward maps were obtained before fieldwork commenced, and random starting points were identified, marked and numbered on the map. This allowed for the random selection of one (if more than one existed) starting point. The field managers concerned will firstly identify where the starting point(s) is/are on the ground. Oncethat has been established he/she will from the starting point count 20 households from the starting point moving to his/her left. The 20th household that he/she has selected was the household were the interviews was supposed to take place Thereafter, the next 20th household was selected and approached until the target number of interviews was obtained.
The following process of household selection was adhered to:
From the starting point 20 houses were counted in a ward. However, if there were:
• 1-5 target number of interviews to be completed in a ward; 01 starting point was used;
• 6-10 target number of interviews to be completed in a ward; 02 starting points were used;
• 11-15 target number of interviews to be completed in the ward; 03 starting points were used;
• 16-20 target number of interviews to be completed in the ward; 04 starting points were used;
• 21-25 target number of interviews to be completed in the ward; 05 starting points were used; and
• 25 and above target number of interviews to be completed in a ward; 06 starting points were used
In the case of a household refusal or if a selected respondent was mentally disabled, the household was immediately substituted with the household on the left. If still there was no interview completed then another substitution, going to the right of the originally selected household, was done. In case of non-contact whereby there was no-one home after two visits at two different times (afternoon and evenings) on the same day, the same substitution method was followed. Therefore, at least two-revisits at different times were done in cases where selected dwelling units, households or individuals were not at home i.e. non-contact. However, in some cases households visited after 19:00 on the day were substituted as agreed to in order to ensure that all the target number of households would be completed in the allocated time per ward.
For the purpose of this study, one randomly selected household respondent was selected per household. All household members qualified if they met the following criteria:
• Resident(s) of the household irrespective of nationality but excluding nonresidents and visitors; and
• 18 years of age or older
• In the event of a child headed household (all household members are under 18 years old), the oldest child was assumed to be the head of household, and should be interviewed
If more than one eligible person was found per dwelling unit, the ideal and most practical and accurate method of random selection of an individual was the use of a KISH grid. One individual per household was selected using the KISH grid after a comprehensive listing exercise was completed of all eligible individuals at the dwelling unit. Once the respondent had been selected the fieldworker will follow up only that person per household. If selected, substitutions could not be made where there were refusals or non-contact over a period of a day after two or more re-visits on the same day.
Dates of Data Collection
Data Collection Mode
Data Collection Notes
Fieldwork commenced on 15 August 2011. Initially there were 5 teams, consisting of 9 field workers and 1 team leader / supervisor per team. The teams generally were broken up 50:50 in ratio of male and female. The second fieldwork teams began on field on 01 September 2011, these were an additional 10 field workers, who were broken up into 2 teams of 5 each.
The third fieldwork team began fieldwork on 17 October 2011. These were an additional 50 resources, which were broken up into 10 teams of 5 each.
A set of “mop-up” teams was assembled by reassigning fieldworkers, as the major work began tapering off, to revisit wards and make up shortfalls in the number of required surveys as best as possible. The first mop-up teams (10 field workers) began in October 2011, with another 20 field workers conducting mop-ups from the November 2011.
The bulk of the fieldwork was complete by the end of November 2011, with a few wards being visited in early December as initial visits, and mopping up going on until 15 December 2011.
The survey instrument (questionnaire) which was used was provided by the GCRO. The instrument was similar to the questionnaire used for the initial Quality of Life survey, with new questions being added only where questions from the previous survey were removed. This was done with the intention of keeping the duration of the survey the same as the initial one. The survey instrument was a 20 page questionnaire, broken up into 12 sections. The bulk of the possible answers were pre-defined, such that most of the survey could be answered using a combination of tick-boxes or by writing down a number answer from a predefined set. To this end there are not many open - ended questions in the survey.
The survey instrument was reformatted by Data World to ensure optimal flow, as well as to cater for the technology platform which was used to conduct the surveys.
The survey company, Data Research Africa, utilised a range of quality control measures during fieldwork for the survey. In the field, fieldworkers checked completed questionnaire schedules immediately after interviews to ensure that all questions were answered and relevant skips were followed. The checked questionnaires were then handed to field or office managers who, whilst in field, performed a second quality check on each questionnaire. They focused on skip patterns, as well as on ensuring that answers corresponded with previous responses and followed a logical process.
University of Cape Town
University of Cape Town
The dataset from the Gauteng City-Region Observatory Quality of Life Survey 2011 is available for use in the DataFirst research data centre at the University of Cape Town.
Gauteng City-Region Observatory. GCRO Quality of Life Survey, 2011.[dataset]. Version 1. Johannesburg: Gauteng City-Region Observatory[producer], 2012. Cape Town: DataFirst [distributor], 2011.
Disclaimer and copyrights
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.