FOOD:LAB
All rights reserved. No part of this publication may be reproduced in any form or by any means without prior permission from the Africa Centre.
©Africa Centre 2015 | 5th Floor Exchange Building, 28 St George’s Mall, Cape Town | [email protected] | www.africacentre.net
Strategic Oversight & Author: Tanner Methvin
Contributor: Etai Even-Zahav | Editor: Tambudzai Ndlovu
Project Management: Robin Jutzen & Tambudzai Ndlovu
Design: Thandiwe Tshabalala | Photography: Yasser Booley
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CONTENTS
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7
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9
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15
18
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65
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132
146
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149
Project Overview
Context
Everyday Urbanism
Food Security Lab
Background
South Africa & Food Insecurity
Urban Food Insecurity & Cape Town
Focus Area
Research Intentions
Research Structure
Spaza Shops
Kanana Residents
Kanana Overview
Perceptions of Behaviour
Actual Behaviour
Motivations for Behaviour
Spaza Shops
Closing Remarks
Acknowledgements
Bibliography
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Everyday African Urbanism is a conceptual framework
that filters out the macro picture of city life and instead
focuses on the micro-spaces of everyday engagement
and interaction.
To re-imagine and re-define the meaning of urban life and
plot a different future/s, we have to first understand what is
actually going on through the practices of the people who
live there. The Africa Centre has applied this framework to
its initial intervention: The Food Security Lab.
To date, The Food Security Lab has comprised 16 months of
research within a community called Kanana in Gugulethu,
Cape Town, South Africa. The research focused on how
people living within households that generally earn a
monthly income of R4,000 or less manage their food
requirements. It examined: why they purchase the food
they do; where they shop and how often; beyond resource
constraints, what influences their food purchasing choices;
at what income level is it possible to secure a high quality
regular diet; and what are the environmental, social and
psychological factors that may prevent a strategic approach
to food purchases and consumption? At the centre of this
research was an exploration of how the local/immediate
food suppliers (spaza shops1, street vendors, informal
cooking facilities) contribute to the food ecosystem. As
such, the Lab also included an in depth review of the spaza
shops in particular, the stock they carry and why, their
supply chains and a range of consumer behaviour within
the shops.
PROJECT OVERVIEW
1. Spaza Shops are informal general stores typically operating out of shacks outside the public sector’s regulatory framework. 5
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7
Urbanisation can be defined as the rapid and
massive growth of, and migration to, large cit-
ies. We are currently experiencing the second
most important period of urban growth and
transition in the history of the world and this
process is almost entirely localised within the
Global South.
Statisticians have been measuring this transi-
tion since 1950 and expect it to continue until
approximately 2030. Over this period the Global
South is expected to grow the urban share of its
populations from 18% to 60%.
Although today 40% of Africa is officially urban-
ised this figure hides enormous discrepancies
across the continent - certain countries (all of
the large African economies) and regions have
already reached the 50% mark while others lag
far behind. However, the reality of African ur-
banisation disproves the generally accepted
principle that economic prosperity is associ-
ated with higher rates of urbanisation. In fact,
Sub-Sahara Africa (SSA) which represents over
90% of the continent, has the largest population
in the world today living in slums and the most
extreme depths of deprivation within these com-
munities. Cities and towns in Africa have been
growing in tandem with slums and informal eco-
nomic activity.
In 2014 the United Nations reported 70% of Afri-
can urban dwellers live in slums and in SSA, only
30% of the population is linked to an electricity
network; 60% to portable water; and 31% have
access to sanitation. The reason Africa’s rapid
urbanisation has translated into the explosion
of poverty, slum-living, and gross inequity is, of
course, complex and manifold. One clear mate-
rial issue that seems poorly understood within
this complexity is the lack of competent theory,
which underpins policies and programmes, and
effective implementation and governance of
these programmes at multiple levels of public
and private sector leadership - city, regional and
national.
It is clear to us today that on one hand much of
public and private sector leadership in Africa is
using policy frameworks and social and environ-
mental interventions that are flawed and which,
by and large, are unable to come to terms with
the reality and implications of rapid urbanisation.
To support alternative approaches to the Conti-
nent’s urban development trajectory, a new body
of theory and practice must be considered. In
other words, unless we can imagine and develop
a more credible account of everyday urbanism,
the desire for urban improvement will remain a
frustrated yearning.
EVERYDAY URBANISMA significant resource of literature dealing with
everyday urbanism asserts that we have to first
understand what is actually going on through the
practices of the people who live in urban spaces
before solutions are defined and implemented.
The principle being that more often than not,
theory is developed in the abstract and remains
without practical application. How can we pos-
sibly expect to address the broad continuum
of challenges facing the urban poor if we don’t
have an intimate understanding of their desires,
aspirations, attachments, connectivity, and mo-
tivations?
CONTEXT
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To bring the ideas of Everyday Urbanism into
practice, as a means of understanding a specif-
ic aspect of urban behaviour we designed the
Food Security Lab research initiative.
It is our intention that the information and knowl-
edge generated out of this process will support
policy, programmes and solutions to the food se-
curity challenges facing our country.
BACKGROUNDThe Millennium Development Goals (MDGs)
placed the need to “eradicate extreme poverty
and hunger” by 2015 at the top of the interna-
tional community’s agenda to improve the grim
state of human health, equity and dignity.
On both accounts, that is, poverty and hunger,
there have been encouraging gains in recent
years. The MDGs indicate that there were 700 mil-
lion less people living in extreme poverty in 2010
as in 1990. Likewise, the latest Food and Agricul-
ture Organisation’s (FAO) report on the State of
Food Insecurity in the World shows a reduction
of chronic undernourishment of 209 million be-
tween today and 1990-19921.
Yet, these big statistics tell a partial story. The
number of people suffering from poverty and
hunger remains unacceptably high after dec-
ades of development efforts: 1.2 billion people are
still estimated to be trapped in extreme poverty,
while 805 million are chronically undernourished1
& 2 .Meanwhile, there is enough wealth and food in
global circulation to support humanity adequate-
ly. It is global disparities, not insufficient resources
that are fundamentally implicated in this human
development crisis. Secondly, these statistics do
not disclose inter-regional differences. Nearly all
of the globe’s destitute and hungry citizenry re-
side in the Global South. Even within the Global
South, wide disparities exist. Sub-Saharan Afri-
ca for instance fares particularly poorly on both
scores compared to the rest of the Global South.
Thirdly, because the MDGs cover such a wide
suite of developmental issues, the measures used
to assess progress have to be simple and well-
established, so that retrieving data across differ-
ent countries would be possible. In the process,
they are inherently forced to make broad estima-
tions and to omit a range of important details.
These span from macro-trends to intra-regional
variations, to micro-scale, context-specific coping
strategies.
Hunger, or more technically ‘undernutrition’, of-
fers a pertinent example of a simplified measure
that only tells a small part of a complex story – im-
portant as it is. Inadequate nutrition, or ‘malnutri-
tion’ manifests in often invisible and counter-intu-
itive ways. For instance, ‘micronutrient deficiency’
or ‘invisible hunger’, a deficiency in vitamins and/
or minerals in the body, affects a large portion
of the world population, with adverse effects on
human wellbeing. Another relatively recent and
counter-intuitive form of malnutrition, ‘over-nutri-
tion’, is commonly believed to manifest in over-
weight and obesity. Globally between 1980 and
2013 the number of overweight and obese people
is estimated to have increased from 857 million to
2.1 billion3. Overweight and especially obesity car-
ry particularly deleterious consequences, ranking
FOOD SECURITY LAB
1. FAO (2014) 2. MDGs (2013:11)3. Ng et al. (2014)
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amongst the top non-communicable health risks.
While traditionally these phenomena were closely
associated with wealth and the Global North, the
rate of the ‘pandemic’ is now growing dramati-
cally in the Global South.
Unlike undernourishment – where some major im-
provements have been made and there are best-
practice examples to draw on – with obesity there
are “…no national success stories” since 1980 as
reported by Ng et al. (2014). There are numerous
factors with direct causal links to obesity ranging
from excessive calorie intake (over-nutrition), to
dietary changes, decreased physical activity and
increasingly, changes in gut microbiome.
Food security looks beyond hunger; “…not as a
deficit of calories, but as a violation of a broader
set of social, economic and physical conditions”4.
It speaks to a wide range of requirements need-
ed to create an enabling environment where “all
people, at all times, have physical and economic
access to sufficient, safe and nutritious food to
meet their dietary needs and food preferences
for an active and healthy life”5. From this defi-
nition, four key pillars can be distilled, namely,
“food availability, physical and economic access
to food, utilisation and stability over time”5.
Mega-trends, such as the second wave of urbani-
sation along with economic globalisation are chal-
lenging conventional conceptions of food secu-
rity. Traditionally, food security focused narrowly
on reducing hunger and improving availability by
increasing rural food production levels. To date, a
clear ‘rural bias’ persists. However, as the Global
South urbanises rapidly, securing urban access
to not only sufficient but also nutritious food, is
becoming a fast-growing but neglected prob-
lem6. Urbanisation, economic globalisation and
concomitant food-chain consolidation (from pro-
ducers through to retailers7) are initiating a ‘nutri-
tion transition’8. Put crudely, this term describes
the shifting of diets that occurs as people switch
from an ‘agrarian’ rural to a more urban ‘industri-
alised’ lifestyle. This shift can, in a small measure,
be associated with a more sedentary lifestyle, but
is likely more related to increased consumption of
energy dense, high fat, high protein, nutrient poor,
highly processed, high in sugar foods. These food
choices are informed by the increased demands
put on urban residents’ time, which leads to the
purchase of cheaper ready made foods, which are
defined by these qualities.
However, since much of the Global South is still
struggling with widespread under nutrition, its
urban centres are increasingly seeing a disturb-
ing co-existence of overweight and obesity. This
stark ‘double burden’ of malnutrition facing
many urban hubs across the African continent
and other parts of the Global South demands
integrated approaches that examine and deal
with food security, and health more generally in
all its dimensions.
4. Patel (2012:2)5. FAO (2014)6. Frayne et al. (2014)7. Reardon & Timmer (2007)8. Popkin et al. (2012)
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SOUTH AFRICA & FOOD INSECURITYSouth Africa offers a telling case-study of this dou-
ble burden and the necessity of developing an in-
tegrated two-pronged approach to food security
that addresses both under nutrition and obesity. It
is important to note that South Africa produces an
adequate supply of food nationally. Yet, clearly pro-
ducing enough food does not automatically secure
access to it, financial or physical. South Africa’s Na-
tional Health and Nutrition Survey (SANHANES-1)9
found that nationally, 26% of its population expe-
rienced hunger while a further 28% were at risk of
hunger. The situation was worse in urban informal
areas, where 32% of the population was found to
be food insecure while 36% was at risk of hunger.
Notably, while the percentage of those experienc-
ing hunger has been halved since 1999, ‘at risk of
hunger’ prevalence has slightly increased. In terms
of obesity and overweight, measured by body mass
index (BMI), prevalence was significantly higher
in females than in males (24.8% and 39.2% com-
pared to 20.1% and 10.6% for females and males,
respectively). A further examination of ‘dietary
intake’ in the Survey “…reflects the classic picture
of the nutrition transition and urbanisation”9. While
the intricacies of this Survey are far more sophisti-
cated than it can be given credit for here, the key
conclusion is that South Africa faces a related nu-
tritional problem that needs to be tackled in an in-
tegrated manner and customised to also cater for
a fast-growing informal urban population. Despite
the fact that South Africa is already 54% urban
(expected to reach 77% by 2050)10 where access
is the main concern, direct food security interven-
tions still focus almost exclusively on production.
URBAN FOOD INSECURITY & CAPE TOWNLooking at national data conceals disparities, es-
pecially in South Africa given its acute levels of so-
cio-economic inequality. Little attention is paid to
the urban dimensions of food security. One excep-
tion is the African Food Security Urban Network
(AFSUN), which conducted an 11-city study in 9
Southern African Countries to evaluate the extent
of urban food insecurity11. Unlike national studies
that survey the entire population, AFSUN focused
on poor households as they tend to be the most
food insecure. Their baseline study found that 77%
of the surveyed households were moderately or
severely food insecure. In Cape Town, which was
one of the 11 cities included in the studies, this rate
was even higher, at 80%12. The informal settlement
of Khayelitsha fared particularly badly, with mod-
erate to severe food insecurity levels at 89%. This
study indicates the pervasiveness of the problem
and shows the urgency of confronting what it calls
the ‘invisible crisis’ of food insecurity among the
urban poor.
Encouragingly, there seems to be a growing ac-
knowledgement of the importance of urban food
security in recent years. In 2013 the City of Cape
Town commissioned a Food System Study to in-
vestigate the contributions of particular areas to
urban agriculture as well as learn more about the
food value chain. The study has yet to be released,
but its findings should enrich current knowledge
and inform further interventions. However, there
is still a significant paucity of research on the
broader ‘food system’ in Cape Town; studies that
9. Shisana et al. (2013)10. UNDP (2014)11. Frayne et al. (2010)12. Battersby (2011)
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evaluate the range of factors that influence food
security once it leaves the farm and before it ar-
rives at the household. The effects of ‘Big Food’,
the multinational food and beverage industry with
huge and concentrated market power, are begin-
ning to be documented, including work on food
deserts13 and supermarket expansion14. Even less
research is available on the ‘small food’ actors and
their impact on community-level food security in
informal settlements. These small actors include a
broad spectrum of traditional as well as contem-
porary mutations of micro-businesses and small
businesses, including spaza shops, independent
food takeaways and street-food vendors.
We have scarcely begun to understand the ‘food
environment’ in the novel context of rapid urbani-
sation and burgeoning informality in South Afri-
ca. Little is understood about how people below
the household income level of R4,000 per month
manage their food requirements. Why do they pur-
chase the food they do? Where do they shop, how
often? Beyond resource constraints, what influenc-
es their food purchase choices? What are the en-
vironmental, social and psychological factors that
may be preventing a strategic approach to food
purchases and consumption within these families?
Understanding the answers to these questions and
modelling alternative solutions to the existing food
purchase and consumption paradigms, provided
the motivation for creating the Food Security Lab
project.
The Lab’s first manifestation focused on an in-
depth review of these questions through the lens
of the spaza shop. Spaza shops proliferate low-in-
come communities in South Africa and often func-
tion as a primary point of access to food sources
within a community. As such, gleaning an in-depth
understanding of what food is made available and
why, what spaza shop customers want, what food
purchase choices they make, what influences these
decisions and how to change both what is sold and
what is consumed can potentially provide greater
insight into the food security challenges facing
South Africa.
13. Battersby & Crush (2014)14. Battersby & Peyton (2014)
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MAP OF KANANA
MAP OF KANANA
FOCUS AREAThe Food Security Lab research focused on an
area called Kanana, a section of the larger com-
munity of Gugulethu in Cape Town. Kanana was
chosen and identified as the site for this study be-
cause of its average household income, housing
type, access to an urban centre, food retailers and
the socio-demographics of the population. These
conditions are similar to many other low-income
communities within South African cities. While the
research from this community cannot provide a
direct blue print for every urban low-income com-
munity, it can progress our knowledge of what is
driving food insecurity and support and inform
other research and interventions in other areas.
Kanana is comprised of 3,177 households, all of which
are shacks; 90% have electricity and 1% have running
water and formal ablution facilities in their backyards.
It is primarily an isiXhosa speaking community with
an average monthly household income of between
R1,000 and R2,000.
KANANA
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23 ha
|<------------------------------------------------------1,02 km------------------------------------------------------>|
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0,18 km
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DURHEIN
GUGULETHU
MONTEVIDEOKING DAVID COUNTRY CLUB
BOQUINAR INDUSTRIAL AREA
Courtesy of the City of Cape Town (2013)
AERIAL VIEW OF KANANA
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AERIAL VIEW OF KANANA
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RESEARCH INTENTIONSThe initial research was designed to explore two
distinct areas:
• The first was related to how spaza shops
function. The intention was to gather data
regarding: what inventory is carried and why;
what sells and why; how prices compare to
other food outlets locally and regionally; who
the customers are; how they make decisions;
the ownership and staffing models; financial
controls; revenue and costs; and other areas
that influence business operations.
• The second related to the Kanana residents
and their food economy. This was designed
to explore all their food related behaviours:
where food is purchased and why; what is
purchased and why; what is spent, when and
why; what external and internal forces influ-
ence those decisions; where food is prepared
and consumed; how their nutritional content
may be compromised and why; beliefs about
health and food; beliefs about the nutritional
value of specific foods and why; the relation-
ships between income, family, gender, age,
weight, employment and other factors and
food; and how eating fits into their broader
financial and social belief and value system.
RESEARCH STRUCTUREPrinciples & ProtocolsA fundamental ethical principle, which guided
the structure of the research was that the com-
munity must be a beneficiary of the research not
simply just in terms of its outcomes, but in the
ways it was conducted. The Africa Centre team
asked itself: if implementing research of this type
is about gathering information from the busi-
nesses and residents of the community, what do
they get in return for providing the data?
In response, the study was structured so that
over 80% of the costs of getting the data were
spent within the community from which it came.
This was achieved by first hiring and training
people from the community to be the research
field officers. They conducted interviews, collect-
ed the participants’ food dairies, and handled all
financial transactions with the participants. The
participating spaza shops and individuals were
also paid a fee for their participation. This com-
bination of factors facilitated an environment of
“fair exchange” between those conducting the
research and those who were being researched.
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SPAZA SHOPSThere are currently 20 spaza shops in Kanana.
Four of these were chosen for inclusion in the
study. These shops were chosen based on three
key factors: location within Kanana, ownership
and size. The shops chosen were all in locations,
which could draw customers from various sec-
tions of the community. The four also varied in
size, so as to be reflective of the total mix of
spaza shops in the area.
The majority of the Spaza shops in the area are
owned by South Africans. However, 10% are So-
mali owned. To ensure any variance in the spaza
shop models that were based on ownership, the
study included three South African and one So-
mali owned shop.
The Spaza shop data was collected in two dis-
tinct ways:
• The first was focused on customer behav-
iour, which was gleaned via structured face
to face interviews and through consumer
observation. Members of the research team
observed consumer behaviour on four oc-
casions for each shop. The researchers ob-
served how the shop was navigated, how
long customers browsed, if at all, and what
was purchased. Interviews were conducted
with customers to gain greater insight into
what motivated their purchasing behaviour
and what they thought about the shop’s
product range and service. The question-
naire used is available under separate cover.
• The second way the data was collected was
from the spaza owners and was gleaned via
interviews. As previously described, the fo-
cus was on understanding the spaza shop’s
operational and financial model.
The Spaza Shop owners were paid R1,000 for
their participation.
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KANANA RESIDENTSInformed by the population size in Kanana, the
study included 348 participants to gain statisti-
cally valid information. This provided a 95% con-
fidence level with a 5% margin of error. Study
participants were recruited at random from vari-
ous public spaces around the four participating
spaza shops. All participants exceeded the age
of 18 years and were asked to respond individu-
ally to a set of surveys and interviews. Willing
participants agreed to an initial intake interview,
keeping a food diary for 30 days and participat-
ing in an exit interview.
The Kanana consumer data was collected in
three distinct phases with different intentions for
each:
• Perceptions of Behaviour – The study be-
gan with a face to face intake process that
asked the participants a range of questions
about their food purchasing and consump-
tion habits. These questions were designed
to gain insight into what the participants be-
lieved to be true about their own behaviour.
In addition, all participants were weighed
and measured. The data from interviews
was gathered by researchers using a mobile
phone based questionnaire that aggregated
all the data onto an online platform and in-
formational dashboards. The questionnaire
used is available under separate cover.
• Actual Behaviour – Participants were re-
quested to maintain detailed food diaries,
which tracked all their eating, drinking and
food purchasing behaviour on a daily basis.
The total period was over a 30-day time-
frame broken into three 10-day blocks of
time. At the end of each 10-day period the
participants returned their diaries to one of
the research field officers. If the data was
deemed to be legitimately collected the par-
ticipant was given the diary forms for the
next 10 days. This process was repeated until
30 days worth of information was collected
for each person. It took 619 people entering
the study to get 348 people who completed
the 30 days of food diaries. Two hundred
and seventy one people (619-348) partici-
pated in the Perceptions of Behaviour part
and completed some days for the Actual Be-
haviour part, but did not complete the full
30 days. The questionnaire used is available
under separate cover.
• Motivations for Behaviour – Once the 30
days of food diaries had been completed,
each participant was interviewed by one of
the research field officers, usually in their
homes, to glean a detailed understanding
of what motivated their eating and purchas-
ing behaviours. This part of the research
attempted to gain and more in-depth un-
derstanding of what affected their behav-
iour and to understand their perceptions of
various food and beverage products. For ex-
ample, it explored for a range of food and
drinks why it was or wasn’t consumed and if
not why, asking: because it is unavailable at
the market, too expensive, they don’t like the
taste, or no one in their households knows
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how to cook it? Regarding food perceptions,
the focus of the interviews tried to determine
what is deemed to be healthy versus unhealthy.
In addition, these interviews also explored
the relative importance of food and eating in
comparison to a broader range of human be-
haviour. For example it compared the value of
eating their favourite meal to watching their
favourite soapie or football match, hanging
out with friends, attending church and other
activities. The questionnaire is available under
separate cover.
After consultation with various Kanana community
members, it was determined that the participants
should be paid as follows: Each participant was
paid R20 for the first interview, R20 for each 10
day period of food diaries completed, and then if
30 days of food diaries were completed an addi-
tional R30 was paid. Those who completed the 30
days and the ‘Motivation for Behaviour’ interview
entered a lottery, which awarded prizes of R250,
R500, R750 and R1,500. This combination of in-
centives proved to work to motivate active and
complete disclosure of information.
Data Collection Timing The data both from spaza shops and Kanana resi-
dents were collected over the period between
September 2013 – August 2014. It was understood
that time of day, day of week, time of the month
and year might affect the information gathered
within each data set. These three factors where
mitigated against by collecting data across a spec-
trum of times of day, days of week and time of the
month. The issues that were considered to be the
most potentially influential were the time of month
and time of year as both of these issues change
how much money is in the household. As residents
are functioning with very little disposable income
the period close to when salaries are paid and so-
cial grants received potentially creates very dif-
ferent food purchasing behaviours compared to
other times of the month. Also, many residents
have temporary work or seasonal employment,
which also can influence what amount of dispos-
able income is available for food based on the time
of year.
The only issue not well protected against in the
study, was the time of year the food diaries were
conducted. All the food diaries were collected over
the period between September and November,
thus any seasonal influences related to income and
food purchasing behaviour may have been influ-
enced by this timeframe.
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KANANA OVERVIEW
The following images provide in-formation, context and insight (e.g. population demographics, service delivery, distribution of trade out-lets and employment statistics) into life in Kanana. If not sited, the statistics presented are derived from the findings of this study.
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PUBLIC ABLUTION FACILITY
BARCELONA
NY 111
PUBLIC TAPS
DISTRIBUTION OF PUBLIC ABLUTION FACILITIES & PUBLIC TAPS AVAILABLE IN KANANA
30% of households have their own ablution facility in their individual backyards.Most residents share a toilet with three other households on the same property.
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11%2%
1%
86%
1%2%4%
91%
1%2%4%
93%
ABLUTION FACILITIES SOURCES OF WATER PIPED WATER
Courtesy of the City of Cape Town (2013)In Cape Town 88.2% of the total population have access to flush toilets. Stats SA (2014)
Courtesy of Stats SA (2014) Courtesy of Stats SA (2014)In Cape Town only 75% of the population have piped water compared to the 89.9% of households in South Africa with access to piped water (Census 2013)
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MONDE SPAZA SHOP
SHEBEENBARCELONA
NY 111
TSHISANYAMA HAIR SALON/BARBER SHOP
SPAZA PUBLIC PHONE
FRUIT & VEG STALL
HOT FOODVENDOR
YIZANI SPAZA SHOP
COME DUZE SPAZA SHOP
LUX SPAZA SHOP
DISTRIBUTION OF TRADEOUTLETS IN KANANA
Food outlets (Spaza shops, Tshisanyamas & Hot food vendors) are largely located along the paths of greatest thoroughfare and human traffic in Kanana.
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68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
TOTAL POPULATION
ETHNIC DISTRIBUTION ACROSS THE POPULATION
Courtesy of the 2011 Census
28
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
2929
TOTAL POPULATION
67
3177
2.45
7830
ETHNIC DISTRIBUTION ACROSS THE POPULATION
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of the 2011 Census
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
Courtesy of the 2011 Census
Courtesy of the 2011 Census
Courtesy of the 2011 Census
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
Courtesy of Stats SA (2014)
LANGUAGES SPOKEN
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign LanguageCourtesy of Stats SA (2014)
29
30
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
MARITAL STATUS
Courtesy of Stats SA (2014)
30
31
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
Courtesy of the 2011 Census
31
32
2%
8%
21%
23%
46%
NUMBER OF PEOPLE IN A HOUSEHOLD NUMBER OF PEOPLE IN A HOUSEHOLD
32
33
68
3177
2.45
7830
TOTAL NUMBER OF HOUSEHOLDS IN KANANA
LANGUAGES SPOKEN
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of Stats SA (2014)
*English, Afrikaans, IsiNdebele, isiZulu. Sepedi, Sesotho, Setswana, XiTsonga, Tshivenda and Sign Language
7762
91%
9%
MARITAL STATUS
1%
20%
1%11%
67%
AVERAGE NUMBER OF PEOPLE LIVING IN A HOUSEHOLD
Courtesy of the 2011 Census
33
2%
98%
SEMI-DETACHED HOUSE
HOUSE/FLAT
HOUSE OR BRICK/CONCRETE
TYPES OF DWELLINGS PEOPLE LIVE IN
Stats SA (2014) 11.4% of households in the City of Cape Town live in informal settlements.
34
TENURE STATUS
22%
5%
97%
Courtesy of Stats SA (2014)
13% of the population in the City of Cape Town occupy houses rent free; 54.1% own their houses; 29.9% rent Stats SA (2014)
TENURE STATUS
Courtesy of Stats SA (2014)13% of the population in the City of Cape Town occupy houses rent free; 54.1% own their houses; 29.9% rent
35
36
19%34%
25%12%10%
Courtesy of the 2011 CensusNearly 35.7% of households in the City of Cape Town live below the poverty line of less than R3500 (Census 2011)
DISTRIBUTION OF MONTHLY HOUSEHOLDINCOME ACROSS THE POPULATION
> R3,201
R1,076 - R3,200
R801 - R1,075R401 - R800R1 - R400
DISTRIBUTION OF MONTHLY HOUSEHOLD INCOME ACROSS THE POPULATION IN KANANA
Courtesy of the 2011 CensusNearly 35.7% of households in the City of Cape Town live below the poverty line of less than R3,500
36
37
10%
0%
20%
30%
60%
50%
40%
70%
80%
90%
100%
46%EMPLOYED
22%NOT ECONOMICALLYACTIVE
4%DISCOURAGEDWORK-SEEKER
EMPLOYMENT STATUS
EMPLOYMENT STATUS OF POPULATION
28%UNEMPLOYED
Stats SA (2014) reports 25.5% of the total population in South Africa are unemployed, with an unemployment rate of 23.9% in Cape Town.Courtesy of Stats SA (2014) Stats SA (2014) reports 25.5% of the total population in South Africa are unemployed, with an unemployment rate of 23.9% in Cape Town.
EMPLOYMENT STATUS OF POPULATION
EMPLOYMENT STATUS
37
3838
PERCENTAGE WHO OWN A MOBILE PHONEPERCENTAGE OF PARTICIPANTS WHO OWN A MOBILE PHONE
38
39
71%
20%
2%
4%
2%
TIME IT TAKES TO FETCH WATER FROM TAPS
TIME IT TAKES TO FETCH WATER FROM TAPS
39
4040
ENERGY FOR COOKING
3%
97%
Courtesy of Stats SA (2014)
ENERGY FOR LIGHTING
1%2%
97%
Courtesy of Stats SA (2014)
94% of the population in the City of Cape Town have electricity for lighting; 85.4% of South African homes have access to electricity Stats SA (2014)
ENERGY FOR COOKING ENERGY FOR LIGHTING
Courtesy of Stats SA (2014) Courtesy of Stats SA (2014)94% of the population in the City of Cape Town have electricity for lighting; 85.4% of South African homes have access to electricity
40
41
PERCEPTIONS OF BEHAVIOUR The data reflected in this section is the result of personal interviews conducted by field workers from the community using a question-naire on their mobile phones. Par-ticipants were also weighed and measured as part of the process so that body mass index scores could be determined. The interviews were conducted in various public spaces in Kanana.
41
42
GENDER
%64 %45MALE FEMALE
GENDER
42
4343
0%
5%
20%
25%
30%
35%
40%
45%
13%AGE: 18 - 24 YRS
41%AGE: 25 - 34 YRS
39%AGE: 35 - 50 YRS
7%
AGE DISTRIBUTION
10%
15%AGE: > 51 YRS
AGE DISTRIBUTION
43
44
BODY MASS INDEX (BMI)
5%
0%
10%
15%
30%
25%
20%
35%
40%
45%
7%UNDERWEIGHTBMI: < 18.5
23%OVERWEIGHTBMI: 25 - 30
31%OBESE BMI: > 30
39%NORMAL WEIGHTBMI: 18.5 - 25
BODY MASS INDEX (BMI)
44
4545
10%
0%
20%
30%
40%
50%
60%
70%
8%
63%
17%
3%
19%29%
49%
GENDER DISTRIBUTION ACROSS FOUR BMI CATEGORIES
12%
UNDERWEIGHT(< 18.5)
NORMAL WEIGHT(18.5 - 25)
OVERWEIGHT(25-30)
OBESE(> 30)
GENDER DISTRIBUTION ACROSS FOUR BMI CATEGORIES
UNDERWEIGHT(BMI: < 18.5)
NORMAL WEIGHT(BMI: 18.5 - 25)
OVERWEIGHT(BMI: 25 - 30)
OBESE(BMI: > 30)
45
PERCENTAGE OF RESPONDENTS WHO GROW THEIR OWN FOOD
4%
46
PERCENTAGE OF PARTICIPANTS WHO GROW THEIR OWN FOOD
46
47
REASONS GIVEN FOR NOT GROWING FOOD
62%
7% 1%
14%
16%
REASONS GIVEN FOR NOT GROWING FOOD
47
48
46%16%
15%
16%
8%WHERE FOOD IS PURCHASED
Spaza: Informal convenience shop; Large Grocery Chain: Such as Shoprite or Pick n’ Pay Only; Other: Unidentified source; Hot Food Vendor: An informal kiosk that sells pre-cooked food; Fruit & Veg stall: An open-air stall largely selling vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically near a butchery to grill meat on an open fire
SPAZA
WHERE FOOD IS PURCHASED
Spaza: Informal convenience shop; Large Grocery Store: Such as Shoprite or Pick n’ Pay Only; Hot Food Vendor: An informal kiosk that sells pre-cooked food; Fruit & Veg stall: An open-air stall largely selling vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically located near a butchery to grill meat on an open fire.
48
9%
42%49%
MAIN REASONS INFLUENCING FOOD PURCHASE CHOICEMAIN REASONS INFLUENCING FOOD PURCHASE CHOICE
49
50
MODE OF TRANSPORT USED TO GET TO FOOD OUTLETS
1%TRAIN
1%WALKING & TRAIN
95%WALKING
2%WALKING & TAXI1%
MODE OF TRANSPORT USED TO GET TO FOOD OUTLETS
50
5151
AVERAGE AMOUNT SPENT ON FOOD PER WEEK
R50
R0
R100
R150
R200
R250
R300 R277
AVERAGE AMOUNT SPENT ON FOOD PER WEEK
51
52
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATED TO HOUSEHOLD MONTHLY INCOME
R100
R0
R200
R300
R400
R500
R600
<R999 R1000 - R2000 R2001 - R3000 R3001 - R4000 >R4000
R184R272
R336R386
R608A
VE
RA
GE
SP
EN
T W
EE
KL
Y
HOUSEHOLD MONTHLY INCOME
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATED TO HOUSEHOLD MONTHLY INCOMEA
VE
RA
GE
SP
EN
T W
EE
KLY
HOUSEHOLD MONTHLY INCOME
<R999 >R4,000R1,000 - R2,000 R2,001 - R3,000 R3,001 - R4,000
R600
R500
R400
R300
R200
R100
R0
52
R50
R0
R100
R150
R200
R250
R300
R350
R323 R253
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO EMPLOYMENT STATUS
AV
ER
AG
E S
PE
NT
WE
EK
LY O
N F
OO
D
EMPLOYED UNEMPLOYED
EMPLOYMENT STATUS
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO EMPLOYMENT STATUS
AV
ER
AG
E S
PE
NT
WE
EK
LY O
N F
OO
D
EMPLOYMENT STATUS
53
54
R299R260
R0
R50
R100
R150
R200
R250
R300
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO GENDER A
VE
RA
GE
SP
EN
T W
EE
KLY
ON
FO
OD
MALE FEMALE
AVERAGE AMOUNT SPENT WEEKLY ON FOOD RELATIVE TO GENDER
AV
ER
AG
E S
PE
NT
WE
EK
LY O
N F
OO
D
54
55
RELATIONSHIP BETWEEN SHOPPING FREQUENCY AND HOUSEHOLD MONTHLY INCOME
MONTHLY
WEEKLY
DAILY
46%
18%
36%< R999
Household monthly income:
Household monthly income:
Household monthly income:
Household monthly income:
18%
52%30%
R1,000 - R2,000
40%42%
18%
R2,001 - R3,000
19%
19%
62%R3,001 - R4,000
RELATIONSHIP BETWEEN SHOPPING FREQUENCY & HOUSEHOLD MONTHLY INCOME
55
56
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
COOK THEIR OWN MEALS DO NOT COOK THEIR OWN MEALS
GENDER RELATIVE TO MEAL PREPARATION
72% 94%
28%
6%
GENDER RELATIVE TO MEAL PREPARATION
COOK THEIR OWN MEALS DO NOT COOK THEIR OWN MEALS
56
57
49%
8%11%
33%
NUMBER OF MAIN MEALS EATEN PER DAY NUMBER OF MAIN MEALS EATEN PER DAY
57
5858
FOOD ITEMS REPORTED TO BE MISSING FROM DIET
26%
57%
17%
FOOD ITEMS REPORTED TO BE MISSING FROM DIET
58
59
32%
WHAT RESPONDENTS WOULD BUY IF GIVEN R100
8%
11%
11%
4% 3%
7%
2%
4%
4%
8%
7% FRUIT & VEG
EGGS
WHAT PARTICIPANTS WOULD BUY IF GIVEN R100
59
6060
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME AND WHERE FOOD IS PURCHASED
FRUIT & VEG STALL
TSHISANYAMA
HOT FOOD VENDOR
LARGE GROCERY STORE
SPAZA
16%
15%
45%16%
8%
13%
20%
41%18%
8%
14%
15%
47%15%
9%
15%
14%
48%
16%7%
< R999
Household monthly income:
Household monthly income:
Household monthly income:
Household monthly income:
R1,000 - R2,000
R2,001 - R3,000 R3,001 - R4,000
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME & WHERE FOOD IS PURCHASED
It should be noted that while the food purchased at Spaza shops decreases by 7% when monthly income increases by four times, food purchased at large grocery stores only increases by 2% when monthly incomes increases by four times.
60
61
RELATIONSHIP BETWEEN BMI AND NUMBER OF MAIN MEALS EATEN PER DAY
UNDERWEIGHT(BMI: < 18.5)
NORMAL WEIGHT(BMI: 18.5 - 25)
OVERWEIGHT(BMI: 25 - 30)
OBESE(BMI: > 30)
Number of main meals eaten per day:
32%
23%
40%
5%31%
21%39%
9%
Number of main meals eaten per day:
32%
20%
40%
8%
Number of main meals eaten per day:
27%
38%
31%
4%
Number of main meals eaten per day:
1 2
3 4
RELATIONSHIP BETWEEN BMI & NUMBER OF MAIN MEALS EATEN PER DAY
61
62
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOMEAND THE NUMBER OF MAIN MEALS EATEN PER DAY
Household monthly income:
Household monthly income:
Household monthly income:
3 MEALS PER DAY
4 MEALS PER DAY
1 MEAL PER DAY
2 MEALS PER DAY
9%
36%48%
7% 10%
55%
7%
28%
11%
36%40%
13% 17%
41%
40%
2%
< R999
Household monthly income:
R1,000 - R2,000
R2,001 - R3,000 R3,001 - R4,000
RELATIONSHIP BETWEEN HOUSEHOLD MONTHLY INCOME & THE NUMBER OF MAIN MEALS EATEN PER DAY
62
63
RELATIONSHIP BETWEEN MAIN MEALS EATEN PER DAY AND THE NUMBER OF HOUSEHOLD MEMBERS
3 MEALS PER DAY
4 MEALS PER DAY
1 MEAL PER DAY
2 MEALS PER DAY
1-2 people
Number of people in household:
3-4 people
Number of people in household:
5-6 people
Number of people in household:
7-8 people
Number of people in household:
16%
39%
40%
4% 9%
31%51%
8%
10%10%
29%50%
11%
30%53%
6%
RELATIONSHIP BETWEEN MAIN MEALS EATEN PER DAY AND THE NUMBER OF HOUSEHOLD MEMBERS
63
6464
%0 50%
34%
31%
32%
33%
< R999
R1,000 - R2,000
R3,001 - R4,000
R2,001 - R3,000
RELATIONSHIP BETWEEN OBESITY AND HOUSEHOLD MONTHLY INCOMEH
OU
SE
HO
LD M
ON
TH
LY IN
CO
ME
RELATIONSHIP BETWEEN OBESITY & HOUSEHOLD MONTHLY INCOMEH
OU
SE
HO
LD M
ON
TH
LY IN
CO
ME
64
6565
ACTUAL BEHAVIOURThe following data was gleaned from individual food diaries kept by the study participants. Participants completed 10 days at a time, three times for a total of 30 days. The information tracked by the participants, was given to the field workers each 10-day period.
It should be noted that the following graphs only record the frequency that particular foods were consumed and NOT the quantity or portion sizes.
65
66
DISTRIBUTION OF FOOD CATEGORIES ACROSS DIFFERENT MEALS OF THE DAY
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
75%
DISTRIBUTION ACROSS FOODCATEGORIES IN THE MORNING
1%1%6%
13%
4%
AM
8%
11%
13%
24%
42%
2%PM
DISTRIBUTION ACROSS FOODCATEGORIES IN THE AFTERNOON
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
GRAIN PROTEIN FRUIT VEGETABLE SNACK DAIRY
Grain: All bran, coco pops cereal, cornflakes, corn flour, maize cereals, oats, porridge, weet bix, pap, umvubo, bread, savoury pie, maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, purl, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
AM PM
TOP 6 FOOD CATEGORIES CONSUMED IN THE EVENING
1%4%12%
15%44%
24%
PM
Grain: All Bran, Coco Pops cereal, Cornflakes, corn flour, maize cereals, oats, porridge, porridge, weet bix, pap, umvubo, bread, savoury pie,'maize, pancakes, umnqusho, samp; Protein: Red meat, chicken, sea food, egg; Fruit: Apple, banana, orange, pear, guava, avocado, assorted other fruits; Vegetable: Potatoes, tomatoes, atchar, aubergine, parmigiana, broccoli, carrot, chakalaka, cucumber, mushroom, pepper, peri peri, soy mince, umfino, mixed vegetables; Snack: Potato and maize based snacks, baked goods, cookies, nuts, chocolate, candy and assorted sweets; Dairy: Yoghurt, cheese.
PM
66
67
TOP 6 FOODS EATEN PER DAY
4%
5%
13%10%
14%
7%
Porridge: Maize or oat based, prepared with hot water or milk. May be sweetened or flavoured; Gwinya: Deep-fried dough balls; Umngqusho: Made of stamp mielies (samp) with beans, butter, and vegetables.
TOP 6 FOODS EATEN PER DAY
Porridge: Maize or oat based, prepared with hot water or milk. May be sweetened or flavoured, Gwinya: Deep-fried dough balls; Umngqusho: Made of mielies (samp) with beans, butter and vegetables.
67
PROCESSED AND UNPROCESSED FOOD CONSUMED AT DIFFERENT TIMES
Processed Foods: Foods whose original, natural state is manipulated or altered in some way; Unprocessed Foods: Typically includes fruit and vegetables.Note: This graph excludes meat products.
14%
86% 73%
27%
71%
29%
68
6969
PROCESSED AND UNPROCESSED FOOD EATEN PER DAY
75%
25%
*Processed Foods: foods whose original, natural state is manipulated or'altered in some way **Unprocessed Foods: Typically includes fruit and vegetables. Note: This graph excludes meat products.
PROCESSED AND UNPROCESSED FOOD EATEN PER DAY
Processed Foods: Foods whose original, natural state is manipulated or altered in some way; Unprocessed Foods: Typically includes fruit and vegetables.Note: This graph excludes meat products.
69
70
TOP 6 FRUITS CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL FRUIT CONSUMPTION
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naatjies, nectarine, paw paw, pineapple, plum, prune, fruit salad, strawberry, watermelon.
39% 30%
4%
14% 5%
3%
TOP 6 FRUITS CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL FRUIT CONSUMPTION
Other: Apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naatjies, nectarine, paw-paw, pineapple, plum, fruit salad, strawberry, watermelon.
70
7171
38%
40%
37%
14%
17%
15%
33%
21%
27%
43%
35%
9%
15%
36%
24%
CONSUMPTION OF TOP 3 FRUITS AS A PERCENTAGE OF TOTALFRUIT INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
38%
40%
37%
14%
17%
15%
33%
21%
27%
43%
35%
9%
15%
36%
24%
CONSUMPTION OF TOP 3 FRUITS AS A PERCENTAGE OF TOTALFRUIT INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
CONSUMPTION OF TOP 3 FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
AGE: 11 - 20 YRS
AGE: 21 - 30 YRS
AGE: 31 - 40 YRS
AGE: 41 - 50 YRS
AGE: > 51 YRS
71
7272
10%
0%
20%
30%
40%
50%
60%
70%
38%
60%
46%
20%
CONSUMPTION OF DIFFERENT FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
31%
13%
4%7%
4%7%
3% 5% 2% 3% 4%2% 1% 1%
NORMAL WEIGHT OBESE
CONSUMPTION OF DIFFERENT FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 30 DAYS BETWEEN NORMAL WEIGHT & OBESE PARTICIPANTS
Other: Apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelon.
TOTA
L F
RU
ITS
72
TOP 3 VEGETABLES CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL VEGETABLES CONSUMED
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables.
11%18.5%
43%
73
7474
CONSUMPTION OF TOP 3 VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
43%
42%
40%
10%
10%
12%
18%
17%
15%
44%
35%
9%
14%
22%
17%
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
MIXED
VEGETABLES
CONSUMPTION OF TOP 3 VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
43%
42%
40%
10%
10%
12%
18%
17%
15%
44%
35%
9%
14%
22%
17%
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
MIXED
VEGETABLES
CONSUMPTION OF TOP 3 VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables.
AGE: 11 - 20 YRS
AGE: 21 - 30 YRS
AGE: 31 - 40 YRS
AGE: 41 - 50 YRS
AGE: > 51 YRS
74
7575
10%
0%
20%
30%
40%
50%
60%
70%
80%
26%
17%
4%
CONSUMPTION OF DIFFERENT VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
6%
Mixed Vegetables: vegetables, salad, stir fry, vegetables; Vegetable soup: Soup prepared with carrots, potatoes, bones, split peas and fresh soup vegetable mix;Other: atchar, aubergine, parmigiana, avocado, broccoli, carrot, chakalaka, cucumber, guacomole, mushrooms, pepper, peri-peri, soya mi nce, Umfino
19%
9%
2% 1%6%
41%
61%
6% 7% 7%
18%
12%
MIXED VEGGIES
KOO
VEGGIESOUP
KOO
NORMAL WEIGHT OBESE
CONSUMPTION OF DIFFERENT VEGETABLES AS A PERCENTAGE OF TOTAL VEGETABLE INTAKE OVER 30 DAYS BETWEEN NORMAL WEIGHT & OBESE PARTICIPANTS
Mixed Vegetables: Vegetables, salad, stir fry vegetables and also typically frozen prepackaged assorted vegetables; Vegetable soup: Soup prepared with carrots, potatoes, bones, split peas and fresh soup vegetabe mix; Other: Atchar, aubergine, parmigiana, avocado, broccoli, carrot, chakalaka, cucumber, guacomole, mushrooms, pepper, peri-peri, soya mince, umfuno.
TOTA
L V
EG
ETA
BL
ES
10%
0%
20%
30%
40%
50%
60%
70%
38%
60%
46%
20%
CONSUMPTION OF DIFFERENT FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
31%
13%
4%7%
4%7%
3% 5% 2% 3% 4%2% 1% 1%
NORMAL WEIGHT OBESE
75
7676
CONSUMPTION OF DIFFERENT PROTEINS AS A PERCENTAGE OF TOTAL PROTEIN INTAKE OVER 30 DAYS
64%13%
12%9%
Red Meat: beef, pork, and mutton products.
EGGS
CONSUMPTION OF DIFFERENT PROTEINS AS A PERCENTAGE OF TOTAL PROTEIN INTAKE OVER 30 DAYS
*Beef and mutton products.
76
CONSUMPTION OF TOP 5 PROTEINS AS A PERCENTAGE OF TOTAL PROTEIN INTAKE OVER 30 DAYS ACROSS DIFFERENT AGE GROUPS
AGE: 11 - 20 YRS
AGE: 21 - 30 YRS
AGE: 31 - 40 YRS
AGE: 41 - 50 YRS
AGE: > 51 YRS 9%
8%
10%
9%
7%
60%
68%
62%
63%
70%
15%
11%
14%
13%
10%
14%
11%
11%
13%
10%
2%
2%
3%
2%
3%
RED MEAT EGGS CHICKEN FISH PORK
77
CONSUMPTION OF DIFFERENT PROTEINS AS A PERCENTAGE OF TOTAL PROTEIN INTAKE OVER 30 DAYS BETWEEN NORMAL WEIGHT AND OBESE PARTICIPANTS
5%
0%
10%
15%
20%
25%
UNSPECIFIEDMEAT
24% 25%
PORK
19%19%
EGGS
10%12%
FISH
8%7%
LIVER
4% 4%
BEEF
3% 2%
TRIPE &OFFALS
1% 1%
FRENCHPOLONY
12%13%
SAUSAGES
6%7%
CHICKEN
11%10%
Unspecified Meats: Participants did not record type of meat
TOTA
L P
RO
TE
INS
10%
0%
20%
30%
40%
50%
60%
70%
38%
60%
46%
20%
CONSUMPTION OF DIFFERENT FRUITS AS A PERCENTAGE OF TOTAL FRUIT INTAKE OVER 3O DAYS BETWEEN NORMAL WEIGHT AND OBESE RESPONDENTS
Other: apricot, berry, fruit salad, cherry, coconut, granadilla, lemon, naartjies, nectarine, paw-paw, pineapple, plum, prune, strawberry, watermelo
31%
13%
4%7%
4%7%
3% 5% 2% 3% 4%2% 1% 1%
NORMAL WEIGHT OBESE
78
TOP 4 SNACKS CONSUMED OVER 30 DAYS
14%
16%
19%
51%
CONSUMPTION OF DIFFERENT CATEGORIES OF SNACKSAS A PERCENTAGE OF TOTAL SNACK IN TAKE OVER 30 DAYS
Maize based snack: Includes crackers, popcorn, Fritos, Nik Naks; Potato based snack: Includes cheese crisps, Pringles and other brands. Baked snack: Includes biscuits, doughnuts, cake, mu�n; Sweets: Includes chocolate, pudding, Tempo, marshmallows
Maize based snack: Includes crackers, popcorn, Fritos, Nik Naks; Potato based snack: Includes cheese crisps, Pringles and other brands; Baked snack: Includes biscuits, doughnuts, cake, muffin; Sweets: Includes chocolate, pudding, Tempo, marshmallows
79
CONSUMPTION OF TOP 5 SNACKS AS A PERCENTAGE OF TOTAL SNACK INTAKE OVER 30 DAYS ACROSS DIFFERENT AGE GROUPS
AGE: 11 - 20 YRS
AGE: 21 - 30 YRS
AGE: 31 - 40 YRS
AGE: 41 - 50 YRS
AGE: > 51 YRS 12%
11%
15%
18%
10%
52%
57%
45%
51%
50%
18%
19%
20%
18%
21%
16%
11%
17%
17%
19%
2%
2%
3%
2%
0%
MAIZE BAKED SNACK POTATO BAKED SNACK BAKED SNACK SWEETS OTHER
Maize based snacks: Includes crackers, popcorn, fritos, nik naks, Potato based snack: Includes cheese, crisps, pringles and other brands; Sweets: Includes chocolate, pudding, mashmallows, Baked snack: Includes biscuits, doughnuts, cakes, muffin; Other: Other unclassified snacks.
80
81
NUMBER OF SNACKS EATEN PER MONTH BY WEIGHT TYPE
Maize based snacks: includes crackers, popcorn, fritos, nik naks; Potato based snack: includes cheese crisps, pringles and other brands; Sweets: includes chocolate, pudding, mashmallows;Baked snack: Other: Other unclassified snacks
2%15%15%19%48%
4%13%7%28%47%
1%17%14%13%54%
2%18%12%19%49%MAIZE BASED
SNACK
POTATO BASEDSNACK
BAKEDSNACK
SWEETS
OTHER
NUMBER OF SNACKS EATEN PER MONTH BY WEIGHT TYPE
Maize based snacks: Includes crackers, popcorn, Fritos, Nik Naks, Potato based snack: Includes cheese, crisps, Pringles and other brands; Sweets: Includes chocolate, pudding, mashmallows, Baked snack: Includes biscuits, doughnuts, cakes, muffin; Other: Other unclassified snacks.
POTATO BASEDSNACK
SWEETS
BAKEDSNACK
OTHER
MAIZE BASEDSNACK
81
TOP 6 BEVERAGES CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL BEVERAGE CONSUMPTION
Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity
TOP 6 BEVERAGES CONSUMED OVER 30 DAYS AS A PERCENTAGE OF TOTAL BEVERAGE CONSUMPTION
14%
9%
11%
13%
18%
30%Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, coke, Cool Drink, soda, Lemon Twist, Fanta, ice tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza,tonic; Juice: Includes fruit concentrates as well as fruit juices in di�erent degrees of purity
82
83
AVERAGE VOLUME OF POPULAR BEVERAGES CONSUMED PER DAY
Soda: appletiser, coca cola, cool crink, soda, lemon twist, fanta, ice tea, jive, iron brew, schweppes, sprite, stoney ginger beer, wizza, tonic. Juice: includes fruit concentrates as well as fruit juices in di�erent degrees of purity.
44ML
265ML
155ML
186ML
188ML
510ML
159ML
AVERAGE VOLUME OF POPULAR BEVERAGES CONSUMED PER DAY
Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity.
83
8484
CONSUMPTION OF POPULAR BEVERAGES AS A PERCENTAGE OF TOTAL BEVERAGE INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
Milk: includes pure milk as well as dairy blends; Soda: appletiser, coca cola, cool drink, soda, lemon twist, fanta, ice tea, jive, iron brew, schweppes, sprite, stoney ginger beer,twizza, tonic; Juice: includes fruit concentrates as well as fruit juices in di�erent degrees of purity; Alcoholic Beverage: umqombothi, cider, wine, gin, beer, irish co�ee, brandy, vodka, whiskey.
31%
28%
30%
32%
26%
18%
21%
18%
16%
21%
15%
13%
14%
15%
16%
13%
14%
13%
12%
10%
12%
10%
12%
12%
15%
10%
10%
9%
9%
10%
3%
3%
3%
3%
2%
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
CONSUMPTION OF POPULAR BEVERAGES AS A PERCENTAGE OF TOTAL BEVERAGE INTAKE OVER 30 DAYS BETWEEN DIFFERENT AGE GROUPS
Milk: includes pure milk as well as dairy blends; Soda: appletiser, coca cola, cool drink, soda, lemon twist, fanta, ice tea, jive, iron brew, schweppes, sprite, stoney ginger beer,twizza, tonic; Juice: includes fruit concentrates as well as fruit juices in di�erent degrees of purity; Alcoholic Beverage: umqombothi, cider, wine, gin, beer, irish co�ee, brandy, vodka, whiskey.
31%
28%
30%
32%
26%
18%
21%
18%
16%
21%
15%
13%
14%
15%
16%
13%
14%
13%
12%
10%
12%
10%
12%
12%
15%
10%
10%
9%
9%
10%
3%
3%
3%
3%
2%
AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 41 - 50 YRS
AGE: 11 - 20 YRS
AGE: >51 YRS
CONSUMPTION OF POPULAR BEVERAGES AS A PERCENTAGE OF TOTAL BEVERAGE INTAKE OVER 30DAYS BETWEEN AGE GROUPS
Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity. Alcoholic Beverage: Umqombothi, cider, wine, gin, beer, irish coffee, brand, vodka, whiskey.
AGE: 11 - 20 YRS
AGE: 21 - 30 YRS
AGE: 31 - 40 YRS
AGE: 41 - 50 YRS
AGE: > 51 YRS
84
CONSUMPTION OF DIFFERENT NON-ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
Soda: appletiser, coca cola, cool drink, soda, lemon twist, fanta, ice tea, jive, iron brew, schweppes, sprite, stoney ginger beer, twizza, tonic; Juice: includes fruit concentrates as well as fruit juices in di�erne degrees of purity; Other: mageu (made from fermented meali pap), energy drinks, hot chocolate, phuzamandla (made from mealie and yeast)
SODA
JUICE
TEA
MILK
COFFEE
4.0L
4.5L
5.0L
0.4L
3.9L
1.0L
4.3L
0.4L
5.3L
0.5L
4.2L
7.6L
13.6L
3.3L
4.9L
5.3L
7.3L
12.6L
5.5L
5.8L
5.2L
8.0L
14.9L
5.0L
6.2L
5.2L
7.5L
15.8LWATER
OTHER
CONSUMPTION OF DIFFERENT NON-ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
Milk: Includes pure milk as well as dairy blends; Soda: Appletiser, Coke, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity
WATER
SODA
JUICE
TEA
MILK
COFFEE
OTHER
85
CONSUMPTION OF DIFFERENT ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
Brandy: Often drank together with beer or sodas so quantities are likely overstated; Spirits: smirno�, whiskey, gin, unclassified vodka, unclassified liquor, irish co�ee
BEER
WINE
BRANDY
CIDER
SPIRITS
0.1L
0.1L
0.2L
1.7L
0.1L
0.0L
0.1L
0.7L
2.3L
0.1L
0.1L
0.2L
0.2L
1.2L
0.0L
0.2L
0.1L
0.1L
0.9L
0.0L
CONSUMPTION OF DIFFERENT ALCOHOLIC BEVERAGES IN LITRES BY WEIGHT CLASS OVER 30 DAYS
Brandy: Often drank together with beer or sodas so quantities are likely overstated; Spirits: smirnoff, whiskey, gin, unclassified vodka, unclassified liquor, irish coffee.
WINE
BRANDY
CIDER
SPIRITS
BEER
86
87
29%
1%
35%
9%
5%
21%
WHERE FOOD AND BEVERAGES ARE PURCHASED
Spaza: Informal convenience shop, Large Grocery Store: Such as Shoprite or Pick ‘n Pay only; Hot Food Vendor: An informal kiosk that sells pre-cooked food; Fruit & Veg Stall: An open-air stall largely vegetables and fruit as well as small confectionary; Tshisanyama: Informal barbecue or braai typically located near a butchery to grill meat on an open fire.
87
8888
TOP 6 FOODS PURCHASED AT THE SPAZA SHOP
6%
27%7%
6%
7%
7%
12%
TOP 6 FOODS PURCHASED AT THE SPAZA SHOP
Red Meat: Includes beef and mutton; Maize Based Snacks: Includes snacks such as popcorn, Fritos, Nik Naks and others; Samp: Dried, stamped, and chopped corn kernels.
88
8989
TOP 6 FOODS PURCHASED AT LARGE GROCERY OUTLETS
17%19%
6% 10%
11%5%
TOP 6 FOODS PURCHASED AT LARGE GROCERY STORES
Red Meat: Includes beef and mutton;Samp: Dried, stamped, and chopped corn kernels; Potatoes: Includes potatoes as well French fries.
89
18%
14%
TOP 6 BEVERAGES PURCHASED AT THE SPAZA SHOP
3%13%21%
29%
90
TOP 6 BEVERAGES PURCHASED AT THE SPAZA SHOPS
Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney Ginger Beer, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity.
90
9191
TOP 6 BEVERAGES PURCHASED AT LARGE GROCERY CHAINS
21%33%
15%
4%
13%12%
TOP BEVERAGES PURCHASED AT LARGE GROCERY STORES
Soda: Appletiser, Coca Cola, Lemon Twist, Fanta, Ice Tea, Jive, Iron Brew, Schweppes, Sprite, Stoney Ginger Beer, Twizza, Tonic; Juice: Includes fruit concentrates as well as fruit juices in different degrees of purity.
91
92
MOTIVATION FOR BEHAVIOUR Once the 30 days of food diaries had been com-pleted, each participant was interviewed by one of the researchers, usually in their homes, to glean a detailed understanding of what motivat-ed their eating and purchasing behaviours. This part of the research attempted to gain a more in-depth understanding of what affected their behaviour and to understand their perceptions of various food and beverage products. In addi-tion, these interviews also explored the relative importance of food and eating in comparison to a broader range of human behaviour.
Note that some questions were repeated again from the ‘Perceptions of Behaviour’ section of this study to test consistency in the answers af-ter the participants had spent 30 days thinking more deeply about their eating behaviour.
92
9393
MAIN HOUSEHOLD DECISION MAKER
69%31%
??
MAIN HOUSEHOLD DECISION MAKER
93
9494
10%
0%
20%
30%
40%
50%
60%
R0 - R999
23%
56%
16%
MONTHLY HOUSEHOLD INCOME
2%3%
R1,000 - R2,000 R2,001 - R3,000 R3,001 - R4,000 > R4,000
MONTHLY HOUSEHOLD INCOME
PE
RC
EN
TAG
E
MONTHLY HOUSEHOLD INCOME
The income distribution is not the same as the census principally because the categories used are different. However, the figures are very close although this information was gathered three years later.
94
9595
GOVERNMENT/SOCIAL GRANT *SUBSIDY RECIPIENTS
*This speaks broadly to government subsidies and social grants that individuals said they receive. The grants cover the gamut - health, housing and childcare.
GOVERNMENT HOUSING SUBSIDY* RECIPIENTS
86%* Individual housing subsidies are available to low-income households, where an applicant wishes to buy a residential property for the first time. It is not a cash pay-out, but is paid directly to a financial institution. Applicants with a household income of less than R3 500, are eligible for a subsidy of R96 362.
95
96
10%
0%
20%
30%
40%
50%
60%
70%
80%
R5 - R10
71%
25%
AVERAGE DAILY SPEND ON AIRTIME
1%
R11 - R20 R21 - R50 R51 - R100
3%
AVERAGE DAILY SPEND ON AIRTIME
10%
0%
20%
30%
40%
50%
60%
70%
80%
R5 - R10
71%
25%
AVERAGE DAILY SPEND ON AIRTIME
1%
R11 - R20 R21 - R50 R51 - R100
3%
PE
RC
EN
TAG
E
AVERAGE DAILY SPEND ON AIRTIME
96
9797
FOOD PREPARATION RELATIVE TO GENDER
76%
24%
FOOD PREPARATION RELATIVE TO GENDER
97
KITCHEN APPLIANCES USED IN FOOD PREPARATION
74%
1%1%4%
20%
KITCHEN APPLIANCES USED IN FOOD PREPARATION
98
FOOD STORAGE AREAS
99
3%
31%
15%2%
49%
38%33%
7% 11% 6%
4%
4%
COOKING METHODS USED
100
PERCEPTIONS OF THE HEALTHIEST METHODS OF PREPARING FOOD
63%9%
12% 7% 3%
2%
4%
101
PERCEPTIONS OF THE UNHEALTHIEST METHODS OF PREPARING FOOD
11%58%
8% 2% 9%
7%
7%
102
29%
71%
FREQUENCY OF GOING TO BED HUNGRY IN THE LAST THREE MONTHS
FREQUENCY OF GOING TO BED HUNGRY IN THE LAST THREE MONTHS
103
104104
PERCENTAGE WHO BORROW (FOOD OR MONEY) EACH MONTH TO FEED THEMSELVES
76%PERCENTAGE WHO BORROW (FOOD OR MONEY) EACH MONTH TO FEED THEMSELVES
104
105105
FREQUENCY WITH WHICH FOOD WAS BORROWED IN THE LAST MONTH
42%
14%
39%
5%
ONCE
TWICE
MORE THAN THREE TIMES
THREE TIMES
FREQUENCY WITH WHICH FOOD WAS BORROWED IN THE LAST MONTH
42%
14%
39%
5%
ONCE
TWICE
MORE THAN THREE TIMES
THREE TIMES
FREQUENCY WITH WHICH FOOD WAS BORROWED IN THE LAST MONTH
105
22%
1%
1%
46%
2%
27%
106
PEOPLE FROM WHOM FOOD IS BORROWED
106
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS RESPONDENTS GAVE FOR EATING
10%
90%
3%
97%
6%
94%
20%
80%
22%
78%
44%
56%
49%
51% 30%
70%
AGREE DISAGREE
REASONS PARTICIPANTS GAVE FOR EATING
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
107
PARTICIPANTS’ UNDERSTANDING OF WHAT HEALTH MEANS
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
AGREE DISAGREE
RESPONDENTS' UNDERSTANDING OF WHAT HEALTH MEANS
3%
97%
6%
94%
22%
78%
44%
56%
10%
90%
20%
80%
49%
51% 30%
70%
6%
94%
22%
78%
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
108
109
PAGES 115 - 120: PERCEPTIONS OF BODY WEIGHT
Each participant of the study was shown the following images:
This self-perception data was then pooled, which provided the means for comparing it to the actual BMI data collected as
part of the study to determine the difference between actual BMI and self perception.
109
110
FEMALE PERCEPTIONS OF WEIGHT
5%
0%
10%
15%
30%
25%
20%
35%
40%
45%
27%UNDERWEIGHTBMI: < 18.5
24%OVERWEIGHTBMI: 25 - 30
8%OBESE BMI: > 30
41%NORMAL WEIGHTBMI: 18.5 - 25
FEMALE PERCEPTIONS OF WEIGHTP
ER
CE
NTA
GE
PERCEIVED WEIGHT
110
111111
10%
0%
20%
30%
40%
50%
60%
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT AND ACTUAL BMI OF FEMALES
24%
41%
27%
3%
19%
29%
8%
49%
UNDERWEIGHT(< 18.5)
NORMAL WEIGHT(18.5 - 25)
OVERWEIGHT(25-30)
OBESE(> 30)
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT & ACTUAL BMI FEMALES
UNDERWEIGHT(BMI: < 18.5)
NORMAL WEIGHT(BMI: 18.5 - 25)
OVERWEIGHT(BMI: 25 - 30)
OBESE(BMI: > 30)
PE
RC
EN
TAG
E
When reviewing the participants’ perceptions of their weight and health it is imperative that an afro-centric lens is considered. The ‘Afro-centric aesthetic’ of-
ten runs counter to the dominant Western cultural values regarding health, weight and beauty. As such, the larger social, cultural and political context within
which participants are making food choices and weight preferences greatly influences their self-perception.
111
112
10%
0%
20%
30%
40%
50%
60%
MALE PERCEPTIONS OF WEIGHT
3%OVERWEIGHT
52%UNDERWEIGHT 46%
NORMAL WEIGHT
0%OBESE
BMI: < 18.5
BMI: 25 - 30BMI: > 30
BMI: 18.5 - 25
MALE PERCEPTIONS OF WEIGHT
PE
RC
EN
TAG
E
PERCEIVED WEIGHT
112
113
10%
0%
20%
30%
40%
50%
60%
70%
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT AND ACTUAL BMI OF MALES
3%
46%52%
8%
63%
17%
0%
12%
UNDERWEIGHT(BMI < 18.5)
NORMAL WEIGHT(BETWEEN 18.5 - 25)
OVERWEIGHT(BETWEEN 25-30)
OBESE(BMI > 30)
RELATIONSHIP BETWEEN PERCEIVED BODY WEIGHT & ACTUAL BMI OF MALESP
ER
CE
NTA
GE
UNDERWEIGHT(BMI: < 18.5)
NORMAL WEIGHT(BMI: 18.5 - 25)
OVERWEIGHT(BMI: 25 - 30)
OBESE(BMI: > 30)
113
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
REASONS TO PURSUE A HEALTH LIFESTYLE
REASONS TO PURSUE A HEALTHY LIFESTYLE
2%
98%
4%
96%
7%
93%
6%
94%
58%
42% 35%
65%
AGREE DISAGREE
114
115
* Consumption of fruit & veg, meat, water** Respondents frequently answered that a healthy lifestyle meant drinking milk, gardening, going to the doctor, watching TV
METHODS BELIEVED TO IMPROVE HEALTH
50%
4% 2% 2%
42%
* Consumption of fruit & veg, meat, water** Respondents frequently answered that a healthy lifestyle meant drinking milk, gardening, going to the doctor, watching TV
METHODS BELIEVED TO IMPROVE HEALTH
50%
4% 2% 2%
42%
METHODS BELIEVED TO IMPROVE HEALTH
*Consumption of fruit & veg, meat and water.**Respondents frequently answered that a healthy lifestyle meant drinking milk, gardening, going to the doctor, watching TV.
115
116
10%
0%
20%
30%
40%
50%
60%
70%
80%
90%
100%
10%
0%
20%
30%
40%
50%
60%
70%
80%
90%
100%
COMPARISON OF THOSE WHO CONSIDER THEMSELVES HEALTHY AGAINST ACTUAL BMI VALUES
PARTICIPANTS WHO CONSIDERTHEMSELVES HEALTHY
PARTICIPANTS WHOARE NORMAL WEIGHT
PARTICIPANTS WHO CONSIDERTHEMSELVES UNHEALTHY
PARTICIPANTS WHO ARE UNDERWEIGHT, OVERWEIGHT & OBESE
88%
39%
12%
69%
COMPARISON OF THOSE WHO CONSIDER THEMSELVES HEALTHY AGAINST ACTUAL BMI VALUES
PE
RC
EN
TAG
E
116
117117
PERCEIVED HEALTH VALUE OF LOCAL DISHES
10%59%30%
3%3%95%
4%8%88%
1%3%95%
20%47%33%
11%13%76%
2%3%95%
Magwinya: Deep-fried traditional South African pastry; Isidudu: Pumpkin pap; Umvubo: Maize Meal & Sour Milk; Umngqusho: Samp & Beans; Umfino: Wild Leaves; Amanquina: Chicken Feet; Mnqambula Cow Head & Pap; Isibindi: Liver
4%3%93%
17%26%57%
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF LOCAL DISHES
Amagwinya: Deep-fried traditional South African pastry, Isidudu: Maize meal; Umvubo: Maize meal & sour milk; Umngqusho: Samp & beans; Umfino: Spinach, cabbage and mealie meal; Amanqina: Chicken feet; Mnqambula: Cow head & pap; Isibindi: Liver.
117
118118
40%
19%
43%
64%
12%24%
82%
11%7%
PERCEIVED HEALTH VALUE OF SWEETS & SNACKS
Amavovo: (Widtjips) Chicken - Crisps;Flyers Cheese & Onion:
44%47%
20%16%
36%37%
69%
12%18%
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF SWEETS & SNACKS
Amavovo: (Widtjips) Chicken-crisps; Flyers: Puff corn snack.
118
119119
PERCEIVED HEALTH VALUE OF FAST FOOD
Umbengo: Traditionally barbecued tripe;Russian Roll: Bread roll filled with sausage made from ground beef
12%
35%
35%
34%
53%
30%
17%30%54%
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF FAST FOOD
Umbengo: Traditionally barbecued tripe;Russian Roll: Bread roll filled with sausage made from ground beef.
119
120
PERCEIVED HEALTH VALUE OF FRUITS
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF FRUITS
120
121121
95%1%5%
PERCEIVED HEALTH VALUE OF CERTAIN VEGETABLES
94%1%
5%
93%1%
6%
91%1%
8%
1%5%
94%
2%7%
91%
1%8%
92%
92%1%
7%90%
1%9%
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF CERTAIN VEGETABLES
121
122122
PERCEIVED HEALTH VALUE OF CERTAIN VEGETABLES AND LEGUMES
90%1%9%
87%1%12%
PEA-NUTS
PEA-NUTS
PEA-NUTS
PEA-NUTS
PEA-NUTS NUTS
GREENBEANS
GREENBEANS
GREENBEANS
GREENBEANS
GREENBEANS
GREENBEANS
89%1%10%
GREENPEAS
GREENPEAS
GREENPEAS
GREENPEAS
GREENPEAS
GREENPEAS
BAKEDBEANS
BAKEDBEANS
BAKEDBEANS
BAKEDBEANS
87%1%12%
BAKEDBEANS
IMANASOYAMINCE
IMANASOYAMINCE
IMANASOYAMINCE
IMANASOYAMINCE
IMANA
SOYAMINCE
81%1%18%
IMANASOYAMINCE
82%1%17%
82%1%17%
KIDNEYBEANS KIDNEY
BEANSKIDNEYBEANS
80%1%
19%
LENTILS
KOO
LENTILS
KOO
79%1%20%
LENTILS
KOO
DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF CERTAIN VEGETABLES & LEGUMES
122
123
PERCEIVED HEALTH VALUE OF CERTAIN BEVERAGES
* Fermented maize meal drink (non alcoholic)
2%3%
95%
3%
6%
91%
1%
2%
97%
8%
18%
74%
9%
20%
71%
6%
10%
84%DONʼT KNOW
UNHEALTHY
HEALTHY
PERCEIVED HEALTH VALUE OF CERTAIN BEVERAGES
*Fermented maize meal drink (non alcoholic).
123
124
20%
31%
49%
18%
64%
18%
16%
68%
17%
17%
68%
16%
* Fruit flavoured juice concentrate
25%
58%
17%
DONʼT KNOW
UNHEALTHY
HEALTHY14%
33%
53%
82%
6%
12%
PERCEIVED HEALTH VALUE OF CERTAIN BEVERAGESPERCEIVED HEALTH VALUE OF CERTAIN BEVERAGES
*Fruit flavoured juice concentrate.
124
COMPARATIVE VALUE PLACED ON EATING FAVOURITE MEALS AGAINST OTHER ACTIVITIES
73%
27%
52%
48%
36%
64%
26%
74%
49%
51%
36%
64%
1%
99%99%
1%
COMPARATIVE VALUE PLACED ON EATING FAVOURITE MEALS AGAINST OTHER ACTIVITIES
COMPARATIVE VALUE PLACED ON EATING FAVOURITE MEALS AGAINST OTHER ACTIVITIES
73%
27%
52%
48%
36%
64%
26%
74%
49%
51%
36%
64%
1%
99%99%
1%
COMPARATIVE VALUE PLACED ON EATING FAVOURITE MEALS AGAINST OTHER ACTIVITIES
73%
27%
52%
48%
36%
64%
26%
74%
49%
51%
36%
64%
1%
99%99%
1%
125
126
PAGE 128- 131: DETOXIFICATION
Although not part of the initial questions
asked, during the ‘Perceptions of Behav-
iour’ part of the study, it emerged that
people believed they needed to clean out
or “flush” their system on a regular basis.
As this issue came up regularly when talk-
ing about eating and drinking behaviour, a
range of questions were added to the final
interviews of all study participants, which
dealt with this behaviour. The following re-
flects what was found.
126
127127
43%
BODY CLEANSING/DETOXIFYING BEVERAGE CONSUMPTION
57%
* Example Ingwe or Stameta
BODY CLEANSING/DETOXING BEVERAGE CONSUMPTION
*Example: Ingwe, Stameta
127
128
2%
POPULAR PRODUCTS PURCHASED THAT ARE BELIEVED TO SUPPORT GOOD HEALTH
2%
4%
7%
15%
62%
9%
Stameta: used to cleanse/detox the blood, colon, liver, kidneys and help with prevention of parasitic infections; Freshen: laxative powder; Ingwe Powder: mild herbal laxative used to detox the body; Epsom salts: used to draw toxins from the bodyMagogota: mild laxative used to cleanse/detox the body
MA
GO
GO
TA
POPULAR PRODUCTS PURCHASED THAT ARE BELIEVED TO SUPPORT GOOD HEALTH
Stameta: Used to cleanse/detox the blood, colon, liver, kidney and help with prevention of parasitic infections, Freshen: Laxative powder; Ingwe Powder: Mild Herbal laxative used to detox the body; Epsom Salts: Used to draw toxins from the body; Magogota: Mild laxative used to cleanse/detox the body.
128
129129
BELIEF THAT VOMITING IS A HEALTHY WAY TO CLEANSE THE SYSTEM
57%43%
BELIEF THAT VOMITING IS A HEALTHY WAY TO CLEANSE THE SYSTEM
129
130
USE OF SUBSTANCES TO INDUCE VOMITING
54%
46%
USE OF SUBSTANCES* TO INDUCE VOMITING
*Substances used to induce vomiting range from herbal teas, to salty water solution to a vinegar concoction.
130
131131
*Laxatives: Spuit or Freshen
RESPONDENTS WHO BELIEVE TAKING A LAXATIVE IS A HEALTHY WAY TO CLEANSE THEIR SYSTEM
49%
PARTICIPANTS WHO BELIEVE TAKING A LAXATIVE* IS A HEALTHY WAY TO CLEANSE THEIR SYSTEM
*Laxatives: Spruit or Freshen
131
132132
SPAZA SHOPSThere are 20 spaza shops in Kanana. The focus of this research was on four of these shops, which included Come Duze, Lux, Monde, and Yizani. The research conducted included: interviews with the spaza shop owners, stock-taking, product sampling, customer interviews and observations which happened on four different days for each spaza shop. These days were spread out over weekdays and weekends, beginning, middle and end of the month, and four months apart. This was done to see if there was any variance in consumer behaviour based on these factors.
132
10%
66%
1%
20%
2%
133
FREQUENCY OF SPAZA SHOP VISITS
133
134
38%
46%
TIMES OF THE DAY PURCHASES ARE MADE AT SPAZA SHOPS
16%
SPAZA
AM
PM
PM
TIMES OF THE DAY PURCHASES ARE MADE AT SPAZA SHOPS
134
135
TIMES OF THE WEEK PURCHASES ARE MADE AT SPAZA SHOPS
55%24%21%
TIMES OF THE WEEK PURCHASES ARE MADE AT SPAZA SHOPS
135
136136
TIME OF THE MONTH PURCHASES ARE MADE AT SPAZA SHOPS
9%
42%49%
TIME OF THE MONTH PURCHASES ARE MADE AT SPAZA SHOPS
9%
42%49%
TIME OF THE MONTH PURCHASES ARE MADE AT SPAZA SHOPS
136
137
10%
0%
20%
30%
40%
50%
60%
80%
AVERAGE SPEND AT SPAZA SHOPS
68%
R1 - R50 R51 - R100 R101 - R150 R151 - R200 > R201
4%
23%
3% 3%
AVERAGE SPEND AT SPAZA SHOPS PER VISIT
PE
RC
EN
TAG
E
AVERAGE AMOUNT SPENT
137
138138
56%
44%
RELATIONSHIP WITH LOCAL SPAZA OWNERRELATIONSHIP WITH LOCAL SPAZA OWNER
138
139
CUSTOMER LOYALTY TO LOCAL SPAZA SHOPS
46%54%
CUSTOMER LOYALTY TO LOCAL SPAZA SHOPS
139
SHOP54% 46%
140
GENDER PROFILE OF CUSTOMERS
140
21%21%19%
8%
31%AGE: 31 - 40 YRS
AGE: 21 - 30 YRS
AGE: 11 - 20 YRS
AGE: 6 - 10 YRS
AGE: 1- 5 YRS
141
AVERAGE CUSTOMER AGE DISTRIBUTION
141
142
10%
0%
20%
30%
40%
50%
60%
70%
80%
90%
CUSTOMER RETAIL BEHAVIOUR IN ALL FOUR SPAZA SHOPS
CUSTOMER RETAIL BEHAVIOUR IN ALL FOUR SPAZA SHOPS
PE
RC
EN
TAG
E
142
143143
42%
5%6%
CIGAR-ETTES
CRISPS CRISPS CRISPS CRISPS
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
CIGAR-ETTES
28%
20%
CRISPS BEER
BREAD
CIGARETTES
AIRTIME
TOP 5 PRODUCTS REPORTEDLY PURCHASED AT SPAZA
143
144
POPULAR PRODUCTS SPAZA OWNERS REPORTED SELLING
20%
13%
13%7%
7%7%
7%
6%6%
CRISPS
JUICE****
POPULAR PRODUCTS SPAZA OWNER REPORTED SELLING
****Includes fruit concentrates as well as fruit juices in different degrees of purity***Non alcoholic fermented beverage**Crushed maize meal*Porridge
144
145145
FRUIT & VEG REPORTED TO HAVE BEEN SOLD BY OWNERS
FRUITS & VEGETABLES REPORTED TO HAVE BEEN SOLD BY SPAZA OWNERS
145
CLOSING REMARKS
What has been discovered through this research both affirms previous studies and unearths a range of new information about food consumption behaviours, beliefs and values amongst the urban poor. It supports the idea that until the desires, aspirations, attachments, and motivations of any community are understood, sustainable solutions to their challenges will not emerge.
146
Our intention remains that the information and knowledge
generated out of this research will support policy,
programmes and solutions to the food security challenges
facing South Africa.
We have deliberately not provided commentary or
developed any firm conclusions about the behaviours and
patterns of participants that emerged from this data. This
choice is principally, because we are not food security
experts nor do we hold an intimate understanding, beyond
this research, of the environment from which this data was
drawn. Our aspiration is that this body of research will
support the needs of others better placed within the food
security, health, and education ecosystems to make more
informed decisions.
It was important for us to stay true to our motivations of
testing the everyday urbanism theories in practice. What
has been discovered through this research both affirms
previous studies and unearths a range of new information
about food consumption behaviours, beliefs and values
amongst the urban poor. It supports the idea that until
the desires, aspirations, attachments, and motivations of
any community are understood, sustainable solutions to
their challenges will not emerge.
147
ACKNOWLEDGEMENTS
Literature Review: Etai Even-Zahav, Elena Geuking & Luke
Metelerkamp (Sustainability Institute)
Statistical Analysis: Brighton Chipuka, Guillaum Doree, Luke
Fostvedt (Iowa State University), Pascal Fröhlicher, Dr. Yoram
Gat, Jorieke Haarhuis, Tsakane Lesea, Garreth Lombard, Adela
Novotna & Gregor Schueler
Field Research: Brighton Chipuka, Felicity Mbambani, Claire
Mollatt, Siyamthanda Mrwebi, Alecia Msila, Nosisi Mzingelwa,
Charity Nonhlanhla Ndimande, Nomzamo Nokoyo, Africa Tole
& Anele Zenzile
Data Entry: Taguekou Alexie, Edwin Uzochukwu Anowi,
Franklin Ondah Awaseh, Adedapo Awotidebe, Nkemngu
Awungiia, Juveta Ayuk, Modele Bitkeu De Bitnga, Thuliswa
Bulana, Jean-Paul De Lange, Rickael Easton, Rosemary Enjema,
Ebot Enih, Samuel Enow, Tulisa Gantsho, Brian Githungo,
Ethell Cikizwa Gqirhana, Kenechukwu Maduka Ikebuaku,
Chouriya Lougue Kabore, Gaelle Fitong Ketchiwou, Arlette
Molako Leufak, Claudia Mukong, Onorine Mujih, Olusola Saibu,
Varlorine Tah, Yves Tchakounte, Zubayr Van Wyk led by
Nguatem Michael Belebema (University of the Western Cape)
The Africa Centre would like to extend its deepest gratitude to the following people for their contributions to this project:
148
149
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