Global Food Security 26 (2020) 100452

Available online 28 October 2020
2211-9124/© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Unhealthy eating practices of city-dwelling Africans in deprived
neighbourhoods: Evidence for policy action from Ghana and Kenya

Michelle Holdsworth a,*, Rebecca Pradeilles b, Akua Tandoh c, Mark Green d, Milkah Wanjohi e,
Francis Zotor f, Gershim Asiki e, Senam Klomegah f, Zakia Abdul-Haq g, Hibbah Osei-Kwasi h,
Robert Akparibo g, Nicolas Bricas i, Carol Auma g, Paula Griffiths b, Amos Laar c

a French National Research Institute for Sustainable Development (IRD), NUTRIPASS Unit: IRD-Univ Montpellier-SupAgro, Montpellier, France
b School of Sport, Exercise and Health Sciences, Loughborough University, UK
c School of Public Health, University of Ghana, Accra, Ghana
d School of Environmental Sciences, University of Liverpool, Liverpool, UK
e African Population and Health Research Center (APHRC), Nairobi, Kenya
f University of Health and Allied Sciences, Ho, Ghana
g School of Health and Related Research, University of Sheffield, Sheffield, UK
h Department of Geography, University of Sheffield, Sheffield, UK
i French Agricultural Research Centre for International Development (CIRAD), Montpellier, France

A R T I C L E I N F O

Keywords:
Eating practices
Unhealthy foods
Food environment
Africa
Ghana
Kenya
Cities

A B S T R A C T

Growing urbanisation in Africa is accompanied by rapid changes in food environments, with potential shifts
towards unhealthy food/beverage consumption, including in socio-economically disadvantaged populations.
This study investigated how unhealthy food and beverages are embedded in everyday life in deprived areas of
two African countries, to identify levers for context relevant policy. Deprived neighbourhoods (Ghana: 2 cities,
Kenya: 1 city) were investigated (total = 459 female/male, adolescents/adults aged ≥13 y). A qualitative 24hr
dietary recall was used to assess the healthiness of food/beverages in relation to eating practices: time of day and
frequency of eating episodes (periodicity), length of eating episodes (tempo), and who people eat with and where
(synchronisation). Five measures of the healthiness of food/beverages in relation to promoting a nutrient-rich diet
were developed: i. nutrients (energy-dense and nutrient-poor -EDNP/energy-dense and nutrient-rich -EDNR); and
ii. unhealthy food types (fried foods, sweet foods, sugar sweetened beverages (SSBs). A structured meal pattern of
three main meals a day with limited snacking was evident. There was widespread consumption of unhealthy
food/beverages. SSBs were consumed at three-quarters of eating episodes in Kenya (78.5%) and over a third in
Ghana (36.2%), with those in Kenya coming primarily from sweet tea/coffee. Consumption of sweet foods
peaked at breakfast in both countries. When snacking occurred (more common in Kenya), it was in the afternoon
and tended to be accompanied by a SSB. In both countries, fried food was an integral part of all mealtimes,
particularly common with the evening meal in Kenya. This includes consumption of nutrient-rich traditional
foods/dishes (associated with cultural heritage) that were also energy-dense: (>84% consumed EDNR foods in
both countries). The lowest socio-economic groups were more likely to consume unhealthy foods/beverages.
Most eating episodes were <30 min (87.1% Ghana; 72.4% Kenya). Families and the home environment were
important: >77% of eating episodes were consumed at home and >46% with family, which tended to be energy
dense. Eating alone was also common as >42% of eating episodes were taken alone. In these deprived settings,
policy action to encourage nutrient-rich diets has the potential to prevent multiple forms of malnutrition, but
action is required across several sectors: enhancing financial and physical access to healthier foods that are
convenient (can be eaten quickly/alone) through, for example, subsidies and incentives/training for local food
vendors. Actions to limit access to unhealthy foods through, for example, fiscal and advertising policies to dis-
incentivise unhealthy food consumption and SSBs, especially in Ghana. Introducing or adapting food-based di-
etary guidelines to incorporate advice on reducing sugar and fat at mealtimes could be accompanied by cooking

* Corresponding author. Joint Research Unit on Food and Nutrition Research in the Global South (UMR NUTRIPASS), French National Research Institute for
Sustainable Development (IRD), 911 av. Agropolis, 34394, Cedex 5, Montpellier, France.

E-mail address: michelle.holdsworth@ird.fr (M. Holdsworth).

Contents lists available at ScienceDirect

Global Food Security

journal homepage: www.elsevier.com/locate/gfs

https://doi.org/10.1016/j.gfs.2020.100452
Received 29 January 2020; Received in revised form 19 August 2020; Accepted 8 October 2020

mailto:michelle.holdsworth@ird.fr
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Global Food Security 26 (2020) 100452

skills interventions focussing on reducing frying/oil used when preparing meals, including ‘traditional’ dishes
and reducing the sugar content of breakfast.

1. Introduction

Africa is experiencing a nutrition transition with changing dietary
habits and food environments related to urbanisation (Imamura et al.,
2015; Agyemang et al., 2016, Holdsworth and Landais, 2019), accom-
panied by rising obesity and diet-related non-communicable diseases
(DR-NCDs) (Naghavi et al., 2017) and persistent micronutrient defi-
ciencies/undernutrition, affecting all socioeconomic groups. Nutrition
transition is characterized by increased consumption of added sugar, fat
(particularly oils), animal-source foods and decreased consumption of
coarse grains, staple cereals and pulses (Popkin and Gordon-Larsen,
2004; Hawkes et al., 2017). Ghana and Kenya typify this dietary and
epidemiological transition (Ghana DHS, 2015; Kenya DHS, 2015;
Rischke et al., 2015; Agyemang et al., 2016; Cira et al., 2016; Ofor-
i-Asenso et al., 2016; 2017; Rousham et al., 2020), which they have
recognised as a pressing public health concern through the development
of national policies to prevent NCDs, incorporating interventions and
policies to promote healthier diets (Ministry of Health Ghana, 2012;
Ministry of Health Kenya, 2015). However, the evidence for developing
policy action within the African region comes mainly from high income
countries and is not tailored for low socioeconomic groups within Af-
rican cities. Therefore, it is important to investigate the eating practices
that people develop in changing urban food environments, so that
context and culturally-sensitive policies and interventions can be
developed; this is difficult to achieve without locally relevant evidence.

The overconsumption of unhealthy diets with a high concentration of
calories and low micronutrients (energy-dense and nutrient-poor
-EDNP), is implicated in the onset of multiple forms of malnutrition
(Pradeilles et al., 2019-a). Eating practices may also evolve in response
to changing contexts (Jastran et al., 2009), such as that accompanying
the nutrition transition. Eating practices are shaped by many social,
material, economic and cultural factors (Warde et al., 2007; Jastran
et al., 2009; Southerton et al., 2011; Warde 2015; Osei-Kwasi et al.,
2020) in people’s food environments and are ‘closely tied to the routines
and rhythms of everyday life’ (Horton et al., 2017). Policies and in-
terventions to promote healthier food consumption may be more
effective when they address the dynamics of eating practices, which
requires an exploration of how food consumption is structured and
organised in social practices (Shove et al., 2012), such as the time of day
and frequency of eating episodes (periodicity), length of eating episodes
(tempo), and who participants eat with and where (synchronisation). The
periodicity with which people eat may have negative effects on health,
for example eating more frequent and irregular meals can have a
detrimental impact on body weight (St-Onge et al., 2017). Periodicity
also includes consumption of specific foods at certain times of the day
that mark the passing of periods of time (breakfast–lunch–dinner)
(Southerton et al., 2011). Tempo is integral to different types of eating
episode, which may, for example, be relatively fast when eating alone
compared with when eating with others (Southerton 2011). Synchroni-
sation requires the co-ordination of people and practices. Eating prac-
tices are usually synchronised with other practices such as work routines
and social lives (Southerton 2011). Hence, by investigating eating
practices in deprived communities in urban Africa, emerging public
policies and recommended interventions can be developed that are
sensitive to the context and therefore more likely to lead to healthier
food environments and the consumption of healthier diets.

There is a lack of evidence about how unhealthy food and beverage
consumption is embedded in everyday life in African cities, including for
the urban poor (Osei-Kwasi et al., 2020). Therefore, the objective of this
study was to ascertain how unhealthy food and beverage consumption is
embedded in everyday life in deprived areas of two African countries, to

identify levers for context relevant policy.

2. Methods

2.1. Ethical approval

Ethical approval for the study was acquired by each institution
involved in the data collection process. In Ghana, ethical approval was
obtained from the Ghana Health Service Ethics Review Committee
(references: GHS-ERC 07/09/16 and GHS-ERC 02/05/17). In Kenya,
ethical approval was obtained from Amref Health Africa (reference:
ESRC P365/2017). The University of Sheffield and Loughborough Uni-
versity recognised both of these ethical review boards as meeting their
ethical standards. Additional ethical approval was obtained from the
University of Liverpool (references: 1434 and 2288) and Loughborough
University (reference: R17 -P142). Written informed consent was ob-
tained from adults and assent from legal guardians of participants <18 y.

2.2. Selecting neighbourhoods and participants

Comparable studies were conducted with adolescents/adults aged
≥13 y (male and female) in deprived neighbourhoods of three rapidly
growing cities in Ghana (Accra and Ho) and Kenya (Nairobi). In Ghana,
James Town was selected from a list of poverty endemic areas in Accra
(CHF International, 2010) and Dome was selected from a list of poor
areas in Ho (UN-HABITAT, 2009). In Nairobi, Makadara was selected
amongst high deprivation areas (Kenya National Bureau of Statistics
et al., 2015) that were judged to be safe to work in by the research team.
To select participants in these low income neighbourhoods, quota
sampling was used to gain a broad sample based on age, body mass index
(BMI), occupation and socio-economic status (SES). These
socio-demographic factors were included to ensure a diverse sample.
The target sample was: n = 294 Ghana (192 in Accra and 96 in Ho); n =
144 Kenya). These quota sampling frames differ because the data from
Ghana combine two separate sister projects (DFC and TACLED) with
different target populations. The DFC project was only conducted in
Ghana (Accra and Ho) whilst the TACLED project was conducted in both
Ghana (Accra only) and Kenya (Nairobi). (Supplementary file 1:
Quota sampling).

To classify participant’s SES for quota sampling, we applied different
methods in Ghana and Kenya. In Ghana, we derived household SES
scores from 13 questions used in the Ghana EquityTool. Household
scores were then compared to the average scores for urban Ghana and
SES quintiles were subsequently derived. Participants were further
classified into three groups: ‘lowest SES’ (1st quintile); ‘low to middle
SES’ (2nd and 3rd quintiles) and ‘high SES’ (4th and 5th quintiles). For
this study, only participants in the 1st and 2nd groups, representing the
‘lowest SES’ and ‘low to middle SES’ were selected. In Kenya, partici-
pants’ SES was derived from their total household expenditure; those
spending <23,674Ksh/month were classified as lowest SES while those
spending 23,674Ksh to 199,999Ksh/month were classified as low-
middle SES based on the Kenya National bureau of Statistics classifica-
tion (2015).

2.3. Assessing food intake

In both countries, an interviewer-led questionnaire was administered
using electronic data capture (CsPro version 6.3/Survey CTO version 2
on a Samsung Galaxy tab-4) to obtain information relating to socio-
demographic characteristics and 24hr food consumption and eating
practices. For the latter, interviewers noted all food and drink consumed

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

by participants in/out-side of the home in the previous 24hr. They also
recorded how long an eating episode lasts (‘tempo’), time of day of the
eating episode (‘periodicity’), who participants eat with and where
(‘synchronisation’) (Supplementary file 2: 24hr recall). To facilitate
data collection, a pre-defined list of food items (Ghana n = 229 and
Kenya n = 270) was inputted into the electronic data collection tem-
plate. The development of these food lists was informed first from an
earlier study in Ghana (Osei-Kwasi et al., 2019-a) and adapted for
Kenya, the subsequent food list was discussed with local partners in all
cities and communities to incorporate their knowledge of food con-
sumption locally. Data were collected between June-December 2017, so
over a 7 month period covering both dry and rainy seasons, therefore
seasonality did not impact on food consumption data. From local
knowledge, the day to day variation of dietary intake is low in the
context of these urban poor communities, meaning that one 24hr recall
is probably a good reflection of eating practices; we also asked partici-
pants whether this was a usual day before beginning the 24 h recall and
arranged to return on another day if it was not.

2.3.1. Categorising foods and beverages
Foods that were consumed were categorised into 26 food groups to

explore how healthy they were and by comparing with those expected
for countries undergoing nutrition transition (Hawkes et al., 2017;
Rousham et al., 2020) (Table 1).

Table 1. List of all foods and beverages consumed.
Five measures of healthiness were used to classify foods (Table 2) in

terms of: i. Their nutrient/energy density; and ii. Based on the unhealthy
types of foods/beverages to prevent DR-NCDs (sweet foods, sugar
sweetened beverages (SSBs) and fried foods). SSBs were defined to
include cold and hot drinks with added sugar as well as non-diet soft
drinks, regular soda, iced tea, sports drinks, energy drinks, fruit punches,
sweetened waters following standard definitions (von Philipsborn et al.,
2019). There is overlap between categories i and ii, but they serve
different purposes. Whilst energy and nutrient density of foods provides
a technically correct classification, it does not tell us about the unhealthy
food groupings, which is particularly useful for communicating public
health interventions, such as developing food-based dietary guidelines
(FBDGs). Therefore, classification into unhealthy food types (Table 2)
was undertaken by categorising individual food items into these types,
based on cooking method and high total fat/sugar content.

Table 2. Classification of foods and beverages into food groups.
Combining the nutrient and energy density information of each

food/beverage allowed us to classify food items as EDNP (represents
‘unhealthy’ foods/beverages). We were also interested in consumption
of energy-dense, nutrient-rich (EDNR) foods/beverages because of their
potential contribution to obesity and DR-NCDs, but also their impor-
tance in providing micronutrients in the context of multiple burdens of
malnutrition in Ghana and Kenya.

Food items were classified as energy dense if >225 kcal/100 g
(WCRF/AICR, 2007). We classified foods based on their nutrient
composition by assigning each food with a nutrient density score to
reflect its nutrient quality based on previously validated approaches (e.
g. Drewnowski, 2005; 2010; Drewnowski and Fulgoni, 2014). The score
incorporated 11 nutrients to encourage (protein, fibre, vitamins A, C, E
and iron, calcium, potassium and magnesium, folate and zinc) and three
nutrients to limit (total fat, total sugars, sodium) based on balancing the
public health nutrition context with the availability of food composition
data for the selected nutrients in Ghana (Abdul-Haq et al., 2018) and in
Kenya. For each food item consumed, nutritional information per 100
kcal for the 11 nutrients and energy density were extracted from a
combination of food composition tables based on their rigour and local
relevance. Nutritional content (both macro- and micro-nutrient infor-
mation) for each of these unique food items was then identified using a
combination of food composition tables) (6 for Ghana and 4 for Kenya).
The primary tables used were: The West African Food Composition
Table (Ghana) and the Kenyan Food Composition

Table 1
Food and beverage items consumed per country.

Food group Food item: Kenya Food items: Ghana

1 Fats and oils (oils,
spreading fats
and fats)

Margarine, butter, peanut
butter, vegetable oil, corn
oil, kimbo/kasuku/
cowboy/chipsy
(vegetable fats)

Palm oil, margarine,
coconut oil

2 Sugar and sweet
spreads

Jam, sugar, sugarcane,
honey, sukari nguru
(molasses)

Sugar, other sugar and
sweet spreads

3 Red meat,
poultry, offals &
giblets

Beef, pork, minced meat,
liver, goat, matumbo
(fried cow/goat
intestines), fried chicken

Pork, fried chicken, boiled
chicken, grilled chicken,
turkey, goat, beef, grilled
beef, fried beef, wele (cow
hide or/feet), liver and
giblets, offal, guinea fowl,
duck

4 Fish and shellfish Fish non-fried/fish fried.
NB. fish consumption was
very low in Kenya so
different types were not
identified

Fish non-fried (barracuda,
tuna, tilapia, salmon,
cassava fish, mudfish,
sardine, kpanla/adziador
(Marine-sourced fish,
usually smoked), fish fried
(tilapia fried, tuna fried,
kyenam (fried fish),
seafood/shellfish (snail,
clams,/adodi, crab,
oysters, octopus), dried fish
(anchovies), canned fish,
smoked fish, kako (salted
fish)

5 Eggs Scrambled egg, poached
egg, fried egg, boiled egg,
omelette

Scrambled egg, fried egg,
boiled egg

6 Processed meat Smokies (precooked
smoked sausage), mutura
(African sausage)

Fried sausage, corned beef

7 Dairy products Milk, sweetened
condensed milk,
unsweetened condensed
milk, soya milk, coconut
milk or cream fermented
milk (maziwa mala
(fermented milk), mursik
(fermented milk
flavoured with charcoal)

Sweetened condensed
milk, powdered milk,
evaporated milk, milk,
flavoured yoghurt, burkina
drink (ground millet/maize
and pasteurized milk)

8 Sweetened tea &
coffee

Sweetened tea,
sweetened coffee

Sweetened tea, sweetened
coffee

9 Sugar Sweetened
Beverages
(except tea/
coffee)

Non-alcoholic beer,
sodas, fruit based drinks,
squashes, cocoa milk
drink (Milo etc)

Light and soft drinks, sodas
and sweetened beverages,
fruit based drinks, cocoa
milk drink (Milo, chocolim,
richoco), Sobolo (hibiscus
tea: dried hibiscus leaves
and sweetened with sugar)

10 Alcoholic
beverages

Beer, wine, spirit Beer, wine

11 Cakes and sweets Doughnut, mandazi
(African doughnut- deep
fried), scone, cake,
biscuits cookies,
chocolate, sweets and
toffee, mabuyu
(sweetened/flavoured
baobab seed), ngumu
(hard cake), pancake

Sweet pie or tart, pastries,
biscuits(imported/local),
chocolate, sweets and
toffee, ice cream,
groundnut cake,
doughnuts, bofrot (dry
doughnuts)

12 Crisps and
crackers

Crisps, chips (snack made
from flour dough fried)

Plantain crisps, chips
(snack made from bread
flour dough fried)

13 Modern mixed
dishes

No consumption Fried rice, fried noodles

14 Traditional
mixed dishes

Githeri (maize & beans),
muthokoi (dehusked
maize & beans), mukimo
(potatoes, vegetable,
pumpkin leaves, maize

Bean stew, eto (boiled
plantain or yam with palm
oil), waakye (cooked rice
and beans meal), red (fried
plantain with bean stew),

(continued on next page)

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

Table (Supplementary file 3: Food composition tables and nutrient
profiling method). Where food composition data were unavailable for
nutrients and/or energy density in any of these tables (38 foods in
Ghana; 2 in Kenya), they were substituted with similar food items agreed
by co-authors (AT, SK, MG, MH, MW, NB, RP). Using USDA dietary
recommendations, the % daily value of all nutrients was calculated per
100 kcal. Nutrient density scores were generated by subtracting the sum
of the nutrients to limit from the sum of the positive nutrients to
encourage. Each food item was categorised as nutrient dense if the

Table 1 (continued )

Food group Food item: Kenya Food items: Ghana

and beans), pilau (rice,
vegetables, spices &
meat), meat stew, fish
stew, vegetable stew

jollof rice, egg stew, garden
egg stew, cabbage stew,
tomato sauce and stew,
okro stew, nkontomire
stew (local spinach stew),
moringa stew (made with
moringa oleifera leaves)

15 Condiments Tomato and chilli sauce
(ketchup), dried chilli,
tomato paste

Shito (a traditional
condiment/very hot
sauce), pepper sauce

16 Wholegrain
cereals

Whole (brown) bread,
local brown rice, whole
meal (brown) chapatti,
whole meal ugali (whole
corn flour meal), whole
meal porridge, boiled
maize, roasted maize

Local brown rice, boiled
corn meal, maize sorghum,
whole grain bread
(seeded), whole (brown)
bread, maize (boiled,
roasted), millet porridge,
other wholegrain cereals

17 Refined cereals White bread, white rice,
noodles, macaroni, white
chapatti, white ugali
(dehusked corn flour
meal), white naan,
refined porridge

White bread (sugar bread,
butter bread, tea bread),
white crisp bread, oats,
white rice, pasta,
macaroni, hot cereals/
porridge/maize porridge/
rice porridge, tapioca,
tombrown (porridge of
roasted corn/cereal flour),
indomie/noodles, hausa
koko (spicy millet
porridge)

18 Roots/tubers not
fried

Bananas (roasted/
boiled), arrowroots,
potatoes (roasted/
boiled), sweet potatoes
(roasted/boiled), yam

Plantain (roasted/boiled),
cassava (boiled), gaari/gari
(cassava powder), yam,
fufu (boiled cassava, yam,
plantain or cocoyam),
Konkonte (fufu made solely
from cassava flour/water)

19 Roots/tubers
fried

Fried potatoes, fried
sweet potatoes, fried
arrowroots, fried
bananas, fried bhajia

Plantain fried, sweet
potatoes fried, yam fried

20 Legumes and
pulses

Beans, lentils, ndengu
(green grams), mbaazi
(pigeon peas), njahi
(black beans)

Baked beans, red beans

21 Nuts and seeds Groundnuts Agushi (melon seeds),
groundnuts

22 Fruit Orange, watermelon, ripe
pawpaw, pineapple,
apple, passion fruit,
banana, lemon, avocado

Aluguntungui (sour soup),
banana, watermelon,
avocado, orange,
pineapple, pear, mango,
coconut, fruit juices
(unsweetened), Pawpaw

23 Vegetables Osuga/sucha/managu
(African nightshades),
cucumber, peppers,
pumpkin, tomatoes, red
or yellow pepper, green
peas, green beans,
carrots, kales, spinach,
eggplant, mushrooms,
onions, chicory, sukuma
wiki (kale), kanzira
(Ethiopian kale), saga
(spider plant), mrenda
(Jute mallow), mitoo
(Bush Okra), garlic,
kunde (cow pea leaves),
terere (amaranth)

Green leaves, spinach,
lettuce, chinese and white
Cabbage, tomatoes,
peppers, carrots,
cucumber, eggplant, green
beans, onions and garlic,
mushrooms, pumpkin,
bottle gourd, okro, turkey
berries, other locally
available leaves and
traditional vegetables

24 Savoury pies Vegetable samosa, meat
samosa,

Meat pie, fish pie, koose
(bean cake; spicy black-
eyed pea fritter)

25 Fermented and
non-fermented
grain products

No consumption Akple (unfermented cereal
meal), T.Z/Tuo Zaafi
(unfermented cereal meal),
kenkey-Ga/Fante
(fermented cereal meal),

Table 1 (continued )

Food group Food item: Kenya Food items: Ghana

banku (fermented cereal
meal), aboloo (fermented
cereal meal), mashed
kenkey (kenkey with sugar,
milk and possibly peanut)

26 Soups Tomato soup, vegetable
soup, bone soup

Ademe soup (made from
leaves of jute plant), light
soup, vegetable soup,
agushie soup (melon
seeds), amma soup (green
leafy vegetable),
groundnut soup, lentil pea
and bean soup, okro soup,
palmnut soup, nkontomire
soup (made from local
spinach leaves), other soup

Table 2
Classification of foods and beverages into unhealthy categories.

Kenya (Nairobi) Ghana (Accra and Ho)

Classification based on nutrient and energy density
EDNP (energy

dense, nutrient-
poor foods)
Energy Dense
(>225 kcals/
100g)Nutrient
Poor
(<10% for
nutrient rich index
score)

Matumbo, mutura honey,
jam, sweets and toffee, sugar,
cake, scone, biscuit cookies,
white chapatti, doughnut,
margarine, butter vegetable
fats/oils fried bhajia, sukari
nguru

Fried red meat (beef, goat,
pork, bush meat, cat meat),
fried chicken, duck, bofrot,
meat pie, fried sausage, TZ,
sugar, sweet spreads,
biscuits, sweets and toffee,
doughnuts, tapioca,
vegetable oil, margarine

EDNR (energy
dense, nutrient-
rich foods)Energy
Dense
(>225 kcals/
100g)Nutrient
Rich
(≥10% for nutrient
rich index score)

Pancake, crisps, mabuyu,
mandazi, ngumu, vegetable/
meat samosa, roasted maize,
local brown rice, wholemeal
chapati, bread, fried chicken,
pork, smokies, peanut butter,
groundnuts, unsweetened
condensed milk

Bread, yam, plantain,
maize, burkina drink,
powdered milk, gari,
konkonte, waakye, koose,
boiled red meat (beef, goat,
pork, bush meat, cat meat),
corned beef, tilapia fried,
octopus, groundnuts

Classification based on food types
Fried foods (fried

through cooking
process)

Fried chicken, fried egg, fried
sausage, koose, fried
octopus, fried plantain/
banana, fried sweet potato/
potato, fried tilapia, fried
yam, fried arrowroots, chips
(flour dough fried),
vegetable/meat samosa,
crisps, fried bhajia

Fried chicken, fried egg,
fried sausage, koose, fried
octopus, fried plantain,
fried sweet potato, fried
tilapia, fried yam

Sweet foods (added
sugars)

Sweets/toffee, chocolate,
sugar, sugarcane, jam,
honey, mandazi, doughnut,
ngumu, scone, biscuit/
cookies, sukari nguru, sugar
cane juice, cake

Sweets/toffee, chocolate,
bofrot, sugar, sweet pie/
tart, tombrown, sugar/
sweets

Sugar Sweetened
Beverages (SSBs)

Sweetened tea/coffee, sodas
sweetened fruit juices,
squash, fruit based drink

Sweetened tea/coffee,
burkina drink, sobolo,
sodas and sweetened
beverages

Full definitions of Ghanaian and Kenyan dishes are in Table 1.

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

nutrient density score was ≥10% and nutrient poor if <10% applying
widely used cut-offs (U.S. Department of Health and Human Services,
2013).

2.4. Assessing eating practices: periodicity, tempo and synchronisation

As an integral part of the 24hr recall (Supplementary file 2: 24hr
recall), questions were asked to assess routines of eating practices in
relation to the time of day and frequency of eating episodes (period-
icity), length of eating episodes (tempo), and who people eat with and
where (synchronisation). An eating episodes was defined as any eating
occasion that involves consumption of any food/beverage (except water
alone) by participants. We chose this term because it reflects the lived
experiences of individuals as part of their daily schedules (Bisogni et al.,
2007).

2.5. Data management and analysis

Data from the 24hr recall interviews were transferred to SPSS version
21. A dictionary of variables was prepared with all variables. 24hr recall
data were then cleaned by checking for missing values and inconsistency
in the data and personal information was also removed. Analysis was
undertaken at an individual person level (frequency of eating for in-
dividuals; age categories, socio-economic status); and at the eating
episode level (EDNP/EDNR score for the eating episode; length of eating
episode; time of day of eating episode). Participants from the two cities
in Ghana were merged for the analysis because we were interested in
eating practices at country, rather than, city level. Descriptive statistics
were calculated and visualised to explore practices in Ghana and Kenya.
Negative binomial regression models were used to analyse the influence
of SES on count of food types consumed for individuals. Statistical an-
alyses were completed using R.

3. Results

We slightly over-recruited based on our target quota sample, with a
total of n = 459 participants (female/and male, adolescents/adults aged
≥13 y) across both countries: Ghana (n = 198 Accra, n = 103 Ho) and
Kenya (n = 158). See Table 3.

3.1. Food group consumption

A list of all food items consumed from the 24hr recall yielded a total
of n = 138 unique foods for Ghana and n = 136 for Kenya (Table 1). In
terms of overall food consumption, we found evidence that nutrition
transition existed in both countries when compared with theories of food
consumption in the context of nutrition transition, but in slightly
different ways (Fig. 1-A). There was widespread consumption of vege-
table oils in Kenya (82.3%), refined cereals in both countries (77.1%
Ghana; 86.1% Kenya), but lower consumption of unrefined wholegrain
cereals (9.6% Ghana; 38.0% Kenya). There was widespread consump-
tion of animal source foods, including fish in Ghana (74.4% Ghana; but
only 1.9% Kenya) and red meat and poultry (especially in Ghana, with
48.8% of the sample consuming them on the previous day, compared
with 27.2% in Kenya). Eggs and dairy product consumption was less
widespread (Fig. 1-A). Fruit and vegetable consumption was higher in
Kenya (43.0% and 93.0% respectively), compared to Ghana (14.3% and
8.0% respectively) (Fig. 1-A). Consumption of legumes/pulses was
higher in Kenya than in Ghana, but in Ghana this did not account for
traditional mixed dishes, stews or soups that contained beans/pulses.
There was widespread consumption of SSBs, including sweetened tea/
coffee in Kenya (72.8% of Kenyans consuming, compared with 11.0% of
Ghanaians) and SSBs (excluding tea/coffee) in Ghana (35.2% of Gha-
naians compared with 13.9% of Kenyans). However, highly processed
food group consumption (processed meats, crisps and crackers) was low
in both countries. Overall, consumption of so called ‘ultra-processed’
food consumption was low in these deprived neighbourhoods in both
countries and was restricted to consumption of noodles, fried sausage,
corned beef, jam, ketchup, tomato paste, SSBs, sweetened milk, cocoa
milk drinks and confectionary.

Fig. 1 here Consumption of food groups and unhealthy foods.

3.2. ‘Unhealthy’ food consumption

Consumption of food and beverages classified as EDNP (e.g. biscuits,
doughnuts, meat pie, fried sausage, sweets and toffee, oils and fats -
Table 1) was widespread, especially in Kenya where 89.9% of eating
episodes contained EDNP items, compared with 55.8% of eating epi-
sodes in Ghana (Fig. 1-B). EDNR foods and beverages (e.g. peanut butter,
plantain, waakye-rice and beans, boiled red meat, mabuyu-baobab fruit
candy- Table 1) were even more widespread, with the majority of par-
ticipants in each county consuming these the previous day (89.4%
Ghana, 84.2% Kenya). In terms of unhealthy food types, over a third of
participants in Ghana (38.5%) compared with over half in Kenya
(57.6%) ate sweet foods in the 24hr period before the interview. SSBs
were consumed at three-quarters of eating episodes in Kenya (78.5%)
and over a third in Ghana (36.2%), with those in Kenya coming pri-
marily from sweet tea/coffee. Two-thirds of eating episodes (66.8%) in
Kenya contained fried foods, compared with 42.4% in Ghana.

We explored whether consumption of these categories of foods
(EDNP, EDNR, sweet foods, SSBs or fried foods) were more or less
common in low or middle SES populations for each country (Supple-
mentary file 4: SES analysis). Our analyses suggested that most un-
healthy categories (especially sweet foods, SSBs or fried foods), were
more commonly consumed in lower SES individuals. Associations were
consistent in both countries. Effect sizes were larger in Kenya compared
to Ghana, suggesting stronger socio-economic influences and in-
equalities operating in Kenya.

3.3. Periodicity of eating practices

A structured meal pattern around three main meals a day in both
countries was evident, as participants reported eating an average of 3.3
times a day in Ghana and 3.7 times in Kenya. (Fig. 2-A). There was
limited snacking in-between meals in Ghana and evidence of an after-
noon snack in Kenya. The eating day started earlier in Ghana: breakfast

Table 3
Socio-demographic characteristics of the sample.

Total (n =
459)

Accra (n =
198)

Ho (n = 103) Nairobi (n
= 158)

n % n % n % n %

Gender
Females 310 67.5 122 61.6 103 100.0 85 53.8
Males 149 32.5 76 38.4 _ _ 73 46.2
Age
13-18y 150 32.7 65 32.8 37 35.9 48 30.4
19-49y 205 44.7 83 41.9 66 64.1 56 35.4
≥ 50y 104 22.6 50 25.3 _ _ 54 34.2
Socio-economic statusa

Lowest 222 48.4 97 49.0 51 49.5 74 46.8
Low to middle 237 51.6 101 51.0 52 50.5 84 53.2
Occupation
In work 193 42.0 74 37.4 37 35.9 82 51.9
In education 76 16.6 28 14.1 16 15.5 32 20.3
Not in work or

education
190 41.4 96 48.5 50 48.6 44 27.8

Body mass index
<25 kg/m2 225 49.1 99 50.2 47 45.6 79 50.0
≥25 kg/m2 233 50.9 98 49.8 56 54.4 79 50.0

a Participants were selected if they were classified as: ‘lowest SES’ (1st quin-
tile); ‘low to middle SES’ (2nd and 3rd quintiles).

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

Fig. 1. Consumption of food groups (A) and unhealthy foods (B).

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

(7–8am), lunch (12-1pm) and dinner (5–7pm), compared with Kenya:
breakfast (8–9am), lunch (1–2pm) and dinner (8–9pm), with a snack
more likely between lunch and dinner in Kenya. We defined breakfast,
lunch and dinner time periods based on the peak times across the sample
in each country.

Fig. 2 Structure and length of eating episodes.
In Ghana, EDNP foods were more commonly consumed during the

morning, whereas in Kenya, EDNP food consumption peaked at meal
times. EDNR food consumption peaked at meal times in Ghana. These
patterns suggest that EDNP foods are a more integral part of meal times
in Kenya, compared with EDNR foods in Ghana (Fig. 3-A). Consumption
of sweet foods peaked in the morning in both countries (Fig. 3-B). In
Ghana, SSBs consumption tended to peak with or just after mealtimes,
whereas in Kenya they peaked at breakfast time and in the afternoon. In
Ghana, fried food was an integral part of all mealtimes, whereas in
Kenya, fried food was particularly common with the evening meal
(Fig. 3-C). SSBs appear to be more common in-between meals in both
countries, but there is also a high consumption of SSBs at breakfast in
Kenya (Fig. 3-B), coming mainly from tea.

Fig. 3 Healthiness of eating episodes throughout the day.

3.4. Tempo of eating practices

In Ghana, the majority of eating episodes were either <10 min
(40.1%) or 10–29 min (47.0%) (Fig. 2-B). People took longer to eat in
Kenya, where less eating episodes were <10 min (21.5%). Longer eating
episodes (≥30 min) were twice as likely in Kenya (27.6% vs 12.9% in
Ghana). Almost one-third (31.5%) of the shortest eating episodes (<10
min) included EDNP foods in Ghana, compared with almost half (49.2%)
in Kenya. In Ghana, sweetened beverages were more likely to be
consumed at shorter eating episodes (17.4% of episodes <10 min v 6%
of episodes ≥30 min). The opposite trend was apparent in Kenya (29.4%
v 39.5% respectively), where SSBs (mostly from sweetened tea/coffee)
were more likely to be consumed at longer eating episodes, suggesting
they are integrated more into family meals. Longer eating episodes were
more likely to have a greater intake of fried food in Ghana (19.6% v 43%
respectively) and EDNP foods in Kenya (49.2% v 56.8% respectively).

3.5. Synchronisation of eating practices

The home environment appeared to be a key setting for shaping food
consumption (Fig. 4-A), given that over three-quarters of eating episodes
were taken at home in both countries (81.9% in Ghana v77.5% in

Fig. 2. Timing (A) and length (B) of eating episodes.

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

Fig. 3. Healthiness of eating episodes throughout the day based on nutrients (A), sweet foods and beverages (B) and fried food (C).

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

Kenya), especially the evening meal in both countries (Fig. 4-A). Longer
meals were also more likely to occur at home. In both countries, street
eating was not a large contributor to food habits, as only 6.3% (Ghana)
and 12.2% (Kenya) of eating episodes were taken on the street; it was
most common in the afternoon (Fig. 4-A). Schools and workplaces were
the least common settings for food consumption in both countries
(7.4–8.5% of food episodes). This low percentage may be because school
feeding programmes in both countries focus on primary schools (so not

on secondary schools with adolescents aged ≥13 years as in our study).
The healthiness of food consumed varied across countries. In Ghana:
unhealthier foods were eaten in schools/workplaces; whereas in Kenya:
unhealthier foods tended to be eaten less often in schools/workplaces
(less EDNP or sweetened beverages) (data not shown).

Fig. 4 Synchronisation of eating practices.
Eating with friends was much less common than with family, as only

7–8.8% of eating episodes were eaten with friends (Fig. 4-B). Fried foods

Fig. 4. Synchronisation of eating practices incorporating where people eat (A) and with whom (B).

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

were almost three times as likely to be consumed when with friends in
Ghana (30.3% in Ghana v 11.5% in Kenya). This was not the case in
Kenya, where sweet foods and SSBs were more commonly consumed
when with friends (sweet foods 23.1% in Kenya v 15.2% in Ghana; SSBs
30.8% in Kenya v 24.2% in Ghana). Breakfast was the most frequent
meal eaten with friends in Ghana, whereas the evening meal in Kenya
was more likely to be shared with friends than other meals (Fig. 4-B).
However, eating alone was also common in both countries, as 41.7% in
Kenya and 45.4% in Ghana of eating episodes were taken alone (Fig. 4-
B). Eating alone was most common at lunchtime in Kenya and in the
evening in Ghana. The role of family was core, as 46.5% in Kenya and
47.3% in Ghana of eating episodes were taken with family. In Ghana,
family mealtimes were less likely to include EDNP foods (24.5%) than in
Kenya (53.4%).

Analysis was also undertaken for sex and age across periodicity,
tempo and synchronisation, but no differences emerged (data not
shown).

4. Discussion

This study investigated how unhealthy food and beverages are
embedded in everyday life in deprived areas of two African countries
(Ghana and Kenya), to identify levers for context relevant policy to
prevent multiple forms of malnutrition.

4.1. Food consumption

We found evidence of unhealthy diets in deprived communities in
both countries, which reflected the types of diets expected in countries
undergoing the nutrition transition, with widespread consumption of
refined cereals in both countries. Animal source foods were commonly
consumed, including red meat, poultry and fish (especially in Ghana).
Consumption of unhealthy food types was common, especially SSBs in
Kenya and fried foods in Ghana. Consumption of EDNP food and bev-
erages was common, especially in Kenya. Commonly consumed EDNP
foods were sugar, coco milk drinks, fried chicken in Ghana and sugar,
vegetable oil and margarine in Kenya. Consumption of EDNR (often
traditional foods associated with cultural heritage) was widespread,
with >84% of the sample consuming these in both countries. Commonly
consumed EDNR foods were fried fish, white sugar/butter bread and
boiled red meat in Ghana and mandazi (African doughnut), white bread
and groundnuts in Kenya. Sweet foods and SSBs were popular in both
countries, but an appreciation of sweetness was evident in Kenya across
all eating occasions, with SSBs coming primarily from sweet tea/coffee
at breakfast and in the afternoon. The Kenya STEPS survey (Kenya Bu-
reau of Statistics, 2015) reported that over a quarter (28%) of Kenyans
always add sugar to beverages. Evidence from a recent systematic re-
view and meta-analysis of 47 studies of dietary behaviours among adults
and adolescents in Ghana and Kenya also found some evidence of
nutrition transition with relatively widespread consumption of animal
source foods (especially red meat and poultry), unhealthy foods and
beverages, and particularly SSBs, which were consumed by 39.9% of the
population in Ghana/Kenya (Rousham et al., 2020).

Consumption of so called ‘ultra-processed’ food and beverages
(Monteiro et al., 2010) was low in the deprived neighbourhoods studied
in both countries. Ultra-processed foods are energy dense and charac-
terized by high levels of free sugar, total/saturated/trans fats, sodium
and low levels of protein and fibre (Monteiro et al., 2010; Moubarac
et al., 2013). ‘Ultra-processed’ food and beverages overlap to some
extent with the classification of EDNP foods and beverages that we used.
But it was regarded as less appropriate for our context as ultra-processed
food does not account for the presence of other beneficial nutrients to
include in the diet, besides fibre. A strength of our approach to cate-
gorising foods was that it is based on previously validated approaches (e.
g. Drewnowski and Fulgoni, 2014) and by including several nutrients to
encourage, it accounts for the context of multiple burdens of

malnutrition. Therefore, taking this approach means that identifying
subsequent interventions can emphasize foods to encourage as well as to
avoid, hence shifting the notion of a ‘healthy’ food-based on the absence
of fat, sugars and sodium to also encompass its content of beneficial
nutrients (Drewnowski, 2005). Low SES groups were more likely to
consume unhealthy foods. It has been postulated that in times of eco-
nomic stress, low SES groups tend to choose cheaper energy-dense foods
to maximize energy value for money, resulting in habitual energy-dense,
nutrient-poor diets (Drewnowski and Specter 2004). Our findings sug-
gest a similar SES gradient to that of high income countries, i.e. low SES
are more likely to consume an unhealthy diet (Allen et al., 2017). A
limitation with using a qualitative 24h recall was that we did not have
data on portion size, which also contributes to energy intake and
therefore needs acknowledging in future interventions and policy. The
use of quota sampling allowed us to include a diverse socio-demographic
background in the selected deprived communities, but a larger quanti-
tative study would have allowed us to explore differences in food con-
sumption within population subgroups, but this was not the purpose of
this study.

There are several limitations with the method used for classifying
foods as unhealthy. The classification of some foods as EDNP was
counter-intuitive and may be a result of the widely used 10% cut off we
used, but it could lead to the classification of some foods as EDNP or
EDNR when they are not, and further validation is required. For
example, in Ghana, meat pies were classified as EDNP because there is a
high ratio of pastry to filling in meat pies, so nutrient density is less than
one may expect from other contexts. This is the same logic behind other
fried meats/sausages. We acknowledge that these foods have positive
nutrients (protein, iron, zinc) but the negative nutrients outweigh them
(either because the overall score for negative nutrients is higher or very
close). Fried chicken was classified as nutrient poor in Ghana because
the nutrient values suggested a higher fat and lower micronutrient
content than the food composition tables used in Kenya, where it was
classified as nutrient rich. This emphasises the challenge of using
different food composition tables, as well as the diversity in nutrient
composition of some foods depending on context. Indeed, this potential
misclassification of foods seems to be a limitation of nutrient only ap-
proaches to classifying foods and beverages, as the classification is
dependent on the accuracy of the food composition foods in the context
where they are used. Not all foods and beverages consumed were listed
in one food composition table for Ghana or Kenya and we had to consult
other food composition tables to complete these for missing foods or
nutrients (outlined in Supplementary File 3).

4.2. Eating practices

A structured meal pattern around three main meals a day in both
countries was evident with limited snacking in-between meals, except in
the afternoon in Kenya. These findings are in line with evidence from a
systematic review (Rousham et al., 2020), in which most individuals and
households had a typical pattern of three meals per day in Ghana and
Kenya. The greater likelihood of a regular afternoon energy dense snack
(usually sweetened tea, with chapatti or mandazi-doughnut in Kenya)
appears to be a reflection of the later timing of the evening meal
compared with Ghana. We need to acknowledge this is part of eating
practices and encourage healthy foods/less sugar at those times through
FBDGs and subsidies on healthier options, like fruit. EDNP foods were a
more integral part of meal times in Kenya, whereas EDNR and fried food
were well integrated into Ghanaian meals. Indeed, the adult Ghanaian
diet is traditionally energy-dense; the main energy-dense component
(grain, cereal, legume or tuber) of the diet is served with soup or stew,
usually accompanied by fish, beef or poultry (Laar and Aryeetey, 2014),
which is characteristic of cultural eating practices of many sub-Saharan
African countries. By ‘traditional’ we draw on a range of definitions of
traditional food that usually evoke cultural or gastronomic heritage,
sharing of knowledge, usually within a country/region (Sebastia, 2017).

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Global Food Security 26 (2020) 100452

In one study of Ghanaians, participants referred to traditional foods as
commonly eaten, culturally acceptable foods associated with national
cultural identity (Osei-Kwasi et al., 2019-b). Defining ‘traditional’ food
and diets is challenging given that colonisation in both countries by the
British has incorporated foods that have been part of diets for more than
a generation. For example, in Ghana, people in the urban south, where
the British predominantly resided, incorporated milk, tea and breakfast
cereals in their regular diet (Tuomainen, 2009), which illustrates the
challenge of defining ‘traditional’.

Most eating episodes were relatively short, as around three-quarters
were <30 min, with people taking longer to eat in Kenya. We have not
identified any similar studies in Africa, but we know from the UK and
European context that the length of time spent eating varies across
cultures. One UK study estimated that over three-quarters (79–83%) of
meals lasted 10–30 min and almost a quarter (17–21%) were longer,
lasting ≥30 min, which is similar to the Ghanaian and Kenyan context
(Cheng et al., 2007). A European study reported that the French spend
almost 3 h/day eating whilst the Finnish, Slovenian, Estonian and
British spend <2 h/day (Warde et al., 2007). They found that time spent
eating has reduced over the previous decades, suggesting we might
expect the same in countries undergoing transition. As we did not collect
data on the exact number of minutes per episode but as a time category,
we are unable to make direct comparisons with these other studies.
Nevertheless, given the distribution of time spent eating, we can
reasonably conclude that in Ghana and Kenya, it is less than in these
European countries.

Almost one-third of the quickest eating episodes (<10 min) included
EDNP foods in Ghana, compared with almost half in Kenya. In Ghana,
sweetened beverages were more likely to be consumed at shorter eating
episodes, but the opposite trend was apparent in Kenya, where SSBs
tended to be consumed at longer eating episodes, suggesting they are
integrated more into family meals. In both countries, longer eating ep-
isodes were more likely to have a greater intake of EDNR foods, fried
food in Ghana and EDNP foods in Kenya. Other studies have reported
that short durations of eating have been attributed to consuming so
called ‘fast foods’ and more snacking and individualized eating
(Southerton 2011). Eating alone was common in both countries,
involving over a third of eating episodes. Nevertheless, street eating was
not a large contributor to food consumption, even though it was twice as
likely in Kenya. One limitation from our study is that we are unable to
identify where food eaten at home was prepared, and it is possible that
food may have been purchased from street vendors but consumed at
home, possibly because work in these deprived communities is more
likely to be informal and close to home. Policy and interventions,
including FBDGs, need to recognise that quick and convenient options
are required that are also healthy and can be eaten alone.

The home environment and the family emerged as an important
setting where healthier eating can be encouraged, with more than three-
quarters of meals consumed at home and almost half of eating episodes
taken with family, which tended to be energy dense and fried/high in
sugar. Eating with friends was much less common than with family. This
was also the case in a US study (Sobal and Nelson, 2003), where authors
report that commensal relationships are primarily with family. Eating
alone was most common at lunchtime in Kenya and in the evening in
Ghana. This did not follow the trend we had expected from studies in
high income countries (Sobal and Nelson, 2003), where people tend to
eat alone more in the day but share evening meals with family. Whilst
eating with families peaked in the evening in Ghana, so did eating alone.
One explanation may be that people’s working lives are less structured
in Ghana and Kenya, so families may not gather together as much in the
evening due to irregular work patterns; possibly because family mem-
bers may arrive home late after work when others have already eaten.
Eating routines tend to be embedded in work and family schedules
(Jastran et al., 2009; Warde, 2015), but one limitation of our study is
that we did not measure working patterns so we are unable to shed light
on their inter-relation with food consumption and eating practices in

these deprived communities in Ghana and Kenya. A strength of our
study was the inclusion of situational information on eating practices
integrated within the qualitative 24hr recall that we have additionally
linked to the healthiness of eating episodes. Most studies of dietary
intake only focus on food/beverage consumption, rather than also
investigating the eating practices around them (Sobal et al., 2012).

Whilst we are unable to generalise to a wider urban population in
both countries, our purpose was to undertake an in-depth investigation
in low income populations who suffer most from multiple burdens of
malnutrition, whilst policy action often ignores SES and is insufficiently
sensitive to the daily lives of the urban poor, but tends to be targeted at
the whole population.

5. Recommendations for policy action and conclusions

In the deprived urban neighbourhoods studied in Ghana and Kenya,
we found widespread consumption of unhealthy foods and beverages,
with high consumption of EDNP, EDNR foods and fried/sweet foods. Our
findings have provided evidence for action in the following three policy
areas:

1.Enhancing financial and physical access to healthier foods that are
convenient (can be eaten quickly/alone) through for example, subsidies and
incentives/training for local food vendors.

We make this recommendation based on our findings that food epi-
sodes are often relatively quick so they need to be healthy and conve-
nient. Local food vendors are omnipresent in the neighbourhood food
environment, as demonstrated by our geographical mapping study on
the physical food environment in these same neighbourhoods (Green
et al., 2020), so they could also play a key role in providing healthy food.
We think that this wider context needs to be acknowledged in the policy
actions we are recommending. We mention financial access because
these are deprived areas, and we know from many studies in Africa,
including our community participatory studies in these same neigh-
bourhoods (Pradeilles et al., 2019-b) that the cost of food is a major
driver of food choice. Indeed we found that sweet foods, SSBs or fried
foods were more commonly consumed amongst the lowest SES cate-
gories in our study.

2. Actions to limit access to unhealthy foods and beverages through, for
example, fiscal and advertising policies to dis-incentivise unhealthy food
consumption, and ’processed’ SSBs, especially in Ghana.

We make this recommendation because we found that ’processed’
SSBs consumption (soft/fruit drinks, sodas and sweetened beverages,
sweetened milk drinks) was widespread, especially in Ghana. We know
from evidence in these same deprived neighbourhoods (Green et al.,
2020) that advertising of SSBs (except tea/coffee) is widespread,
comprising almost half of all advertisements. We also know from wider
research that advertising is an important driver of food choice. We also
know from policy appraisals with national stakeholders in Ghana and
Kenya that food advertising controls are a priority for action (Laar et al.,
2020; Asiki et al., 2020). We recommend actions to dis-incentivise un-
healthy food consumption because we found widespread consumption
of unhealthy foods and beverages, including at mealtimes. Limiting
access to these foods by making healthier foods (such as fruit and veg-
etables) relatively cheaper (through subsidies on healthier foods or taxes
on unhealthy food and beverages) could contribute to a healthier food
environment.

3. Introducing or adapting FBDGs incorporating advice on reducing sugar
and fat at mealtimes accompanied by cooking skills interventions focussing on
reducing frying/oil used when preparing meals, including ‘traditional’ foods/
dishes and reducing the sugar content of breakfast (from foods and drinks).

We found that sweetened beverages were consumed at three-
quarters of eating episodes in Kenya (78.5%) and over a third in
Ghana (36.2%), with those in Kenya coming primarily from sweet tea/
coffee. We also found that EDNP foods and fried foods were an integral
part of meal times in Kenya, compared with EDNR and fried foods in
Ghana. Consumption of sweet foods and SSBs peaked at breakfast in

M. Holdsworth et al.

Global Food Security 26 (2020) 100452

Kenya (just sweet foods increase at breakfast in Ghana). When snacking
occurred (more common in Kenya), it was in the afternoon and tended to
be accompanied by a sweetened drink. In both countries, fried food was
an integral part of all mealtimes, particularly common with the evening
meal in Kenya. SSBs appear to be more common in-between meals in
both countries, but there is also a high consumption of sweetened drinks
at breakfast in Kenya, coming mainly from tea. Therefore, FBDGs need
to acknowledge these directly, for example, making recommendations
for a lower sugar breakfast by reducing sugar in tea in Kenya and sweet
food consumption in both countries; and reducing fat in meals, including
those consumed at home, including ‘traditional’ foods and dishes that
are associated with cultural identity. In Ghana there are no interpretive,
evidence-informed FBDGs despite political support (Laar et al., 2020).
However, Dietary and Physical Activity Guidelines have been adopted
by the Ghana Dietetic Association (MoH 2009), which provide infor-
mation on making healthy choices and planning meals based on the
nutrient content of foods. Kenya has published national Guidelines for
Healthy Diets and Physical Activity that provide generic guidance (MoH,
2017). Both of these guidelines are nutrient focused and do not frame
messages in terms of how or when food is eaten as part of meals. They do
not mention avoiding sweet foods/beverages (at breakfast), fried foods
or SSBs. They also need to account for who people eat with-family meals
or alone and include examples of healthy convenient foods. All this
could be added to extend their reach, including to more deprived
communities.

Funding

This work was supported by two funders in two research projects.
The ‘Dietary transitions in Ghana’ project was funded by a grant from
the Drivers of Food Choice Competitive Grants Programme [grant
number OPP1110043], which is funded by the Bill & Melinda Gates
Foundation and The Foreign, Commonwealth and Development Office
and managed by the University of South Carolina Arnold School of
Public Health, USA. The TACLED project was funded by a Global
Challenges Research Fund Foundation Award led by the MRC [grant
number MR/P025153/1], and supported by AHRC, BBSRC, ESRC and
NERC. The funders played no role in the design of the study, data
collection, data analysis, interpretation of the data or writing of the
publication.

Declaration of competing interest

The authors declare that they have no known competing financial
interests or personal relationships that could have influenced the work
reported in this paper.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.
org/10.1016/j.gfs.2020.100452.

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Unhealthy eating practices of city-dwelling Africans in deprived neighbourhoods: Evidence for policy action from Ghana and ...
1 Introduction
2 Methods
2.1 Ethical approval
2.2 Selecting neighbourhoods and participants
2.3 Assessing food intake
2.3.1 Categorising foods and beverages

2.4 Assessing eating practices: periodicity, tempo and synchronisation
2.5 Data management and analysis

3 Results
3.1 Food group consumption
3.2 ‘Unhealthy’ food consumption
3.3 Periodicity of eating practices
3.4 Tempo of eating practices
3.5 Synchronisation of eating practices

4 Discussion
4.1 Food consumption
4.2 Eating practices

5 Recommendations for policy action and conclusions
Funding
Declaration of competing interest
Appendix A Supplementary data
References