food lab - africa centre

FOOD:LAB

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©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

5

7

7

9

9

12

12

15

18

18

20

22

24

41

65

92

132

146

148

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

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

15

23 ha

|<------------------------------------------------------1,02 km------------------------------------------------------>|

|<---

0,18 km

--->|

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

22

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.

2323

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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


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%

68

3177

2.45

7830


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%

TOTAL POPULATION

ETHNIC DISTRIBUTION ACROSS THE POPULATION

Courtesy of the 2011 Census

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68

3177

2.45

7830


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%

2929

TOTAL POPULATION

67

3177

2.45

7830

ETHNIC DISTRIBUTION ACROSS THE POPULATION


LANGUAGES SPOKEN








7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%


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


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%

MARITAL STATUS


30

31

68

3177

2.45

7830


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%



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


LANGUAGES SPOKEN




7762

91%

9%

MARITAL STATUS

1%

20%

1%11%

67%



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%


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%


ENERGY FOR LIGHTING

1%2%

97%


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:




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





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




OBESE(BMI: > 30)

Number of main meals eaten per day:

32%

23%

40%

5%31%

21%39%

9%


32%

20%

40%

8%


27%

38%

31%

4%


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




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


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


5-6 people


7-8 people


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


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


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%



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%



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


PE

RC

EN

TAG

E


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%


10%

0%

20%

30%

40%

50%

60%

70%

80%

R5 - R10

71%

25%


1%

R11 - R20 R21 - R50 R51 - R100

3%

PE

RC

EN

TAG

E


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


42%

14%

39%

5%

ONCE

TWICE

MORE THAN THREE TIMES

THREE TIMES


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


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


10%

90%

3%

97%

6%

94%

20%

80%

22%

78%

44%

56%

49%

51% 30%

70%

AGREE DISAGREE


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


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


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%

AGREE DISAGREE


3%

97%

6%

94%

22%

78%

44%

56%

10%

90%

20%

80%

49%

51% 30%

70%

6%

94%

22%

78%


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


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




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




OBESE(BMI: > 30)

113


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE


2%

98%

4%

96%

7%

93%

6%

94%

58%

42% 35%

65%

AGREE DISAGREE

REASONS TO PURSUE A HEALTH 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


50%

4% 2% 2%

42%


*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%



73%

27%

52%

48%

36%

64%

26%

74%

49%

51%

36%

64%

1%

99%99%

1%


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%


9%

42%49%


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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