Environ. Res. Lett. 17 (2022) 104043 https://doi.org/10.1088/1748-9326/ac9326
LETTER
Adherence to EAT-Lancet dietary recommendations for health and
OPEN ACCESS sustainability in the Gambia
RECEIVED
4 April 2022 Zakari Ali1,∗, Pauline F D Scheelbeek2,3, Jyoti Felix2, Bakary Jallow4, Amanda Palazzo5,
REVISED Alcade C Segnon6,7,8, Petr Havlík5, Andrew M Prentice1 and Rosemary Green2,3
13 September 2022
1 Nutrition and Planetary Health Theme, MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, The
ACCEPTED FOR PUBLICATION
20 September 2022 Gambia
2 Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
PUBLISHED 3
6 October 2022 Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
4 National Nutrition Agency (NaNA), Banjul, The Gambia
5 International Institute for Applied Systems Analysis, Laxenburg, Austria
Original content from 6 CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), International Crops Research Institute for the
this work may be used
under the terms of the Semi-Arid Tropics (ICRISAT), Bamako, Mali
7
Creative Commons Alliance of Bioversity International and International Center for Tropical Agriculture (CIAT), Dakar, Senegal
Attribution 4.0 licence. 8 Faculty of Agronomic Sciences, University of Abomey-Calavi, Cotonou, Benin
∗
Any further distribution Author to whom any correspondence should be addressed.
of this work must
maintain attribution to E-mail: zali@mrc.gm
the author(s) and the title
of the work, journal Keywords: dietary sustainability, EAT-Lancet diet, diet composition, Gambia, environmental footprint
citation and DOI. Supplementary material for this article is available online
Abstract
Facilitating dietary change is pivotal to improving population health, increasing food system
resilience, and minimizing adverse impacts on the environment, but assessment of the current
‘status-quo’ and identification of bottlenecks for improvement has been lacking to date. We
assessed deviation of the Gambian diet from the EAT-Lancet guidelines for healthy and sustainable
diets and identified leverage points to improve nutritional and planetary health. We analysed the
2015/16 Gambian Integrated Household Survey dataset comprising food consumption data from
12 713 households. Consumption of different food groups was compared against the EAT-Lancet
reference diet targets to assess deviation from the guidelines. We computed a ‘sustainable and
healthy diet index (SHDI)’ based on deviation of different food groups from the EAT-Lancet
recommendations and modelled the socio-economic and geographic determinants of households
that achieved higher scores on this index, using multivariable mixed effects regression. The average
Gambian diet had very low adherence to EAT-Lancet recommendations. The diet was dominated
by refined grains and added sugars which exceeded the recommendations. SHDI scores for
nutritionally important food groups such as fruits, vegetables, nuts, dairy, poultry, and beef and
lamb were low. Household characteristics associated with higher SHDI scores included: being a
female-headed household, having a relatively small household size, having a schooled head of the
household, having a high wealth index, and residing in an urban settlement. Furthermore, diets
reported in the dry season and households with high crop production diversity showed increased
adherence to the targets. While average Gambian diets include lower amounts of food groups with
harmful environmental footprint, they are also inadequate in healthy food groups and are high in
sugar. There are opportunities to improve diets without increasing their environmental footprint
by focusing on the substitution of refined grains by wholegrains, reducing sugar and increasing
fruit and vegetables consumption.
1. Introduction five years suffer from stunted growth or wasting [1]
and micronutrient deficiencies affect over 2 billion
Globally, over 40% of all men and women are people [2]. Furthermore, over the last decade, slow
overweight or obese, 195 million children under progress has been made in meeting global targets
© 2022 The Author(s). Published by IOP Publishing Ltd
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
on maternal and child nutrition; and no country and emphasises consumption of vegetables, fruits,
is currently on course to meet global diet-related wholegrains, legumes and nuts, and unsaturated oils.
non-communicable disease (NCD) targets related The EAT-Lancet diet recommends low consumption
to reducing adult obesity and salt intake [1]. Sub- of red and processedmeat, added sugar, refined grains
optimal diets, resulting from low consumption of and starchy foods.While advocating for a ‘Great Food
nutritious food and high consumption of harmful Transformation’, the Commission recognised that the
foods, are leading risk factors for morbidity andmor- required changes in diets will have to differ by region
tality around the world [3, 4]. Additionally, exist- and from country to country [23]. Therefore, adop-
ing food production systems threaten the health of tion of the reference diet needs to be carefully tailored
the planet and require urgent transformation [5]. to context-specific needs to limit unintended health
The agriculture sector alone is responsible for 70% and environmental impacts [24]. Furthermore, in
of global fresh water use, 23% of greenhouse gas countries such as The Gambia which has co-existing
emissions, and significant soil degradation and biod- undernutrition and overnutrition, the required diet-
iversity loss [6]. ary changes might need to vary among different pop-
Food system inequalities are being exacerbated by ulation groups. For example, despite progress over the
climate change [7]. Low-and middle-income coun- years in reducing undernutrition, one in five children
tries have a reduced capacity to adapt to climate under five years still suffer from stunting and three in
change and will face the harshest impacts from five are anaemic. Increased provision of animal source
low crop yields, high food prices and compromised foods could be important sources of essential nutri-
food utilisation arising from disruptions in house- ents to combat these conditions [25, 26]. At the same
hold drinking water and increased infectious disease time, over 40% of adults are overweight implying
burden [8, 9]. excess provision of calories and a need formoderation
The Gambia, situated on the lower edge of the [27].
Sahel, is highly vulnerable to climate change [10]. It Given these problems and existing government
experiences irregular rainfall patterns and flooding, efforts to improve on undernutrition [28], diet-
together with longer periods of drought, and extreme related chronic diseases and the environment [29],
heat that affect food production and livelihoods [11, it is important and timely to examine national diet-
12]. Consequently, domestic food production is lower ary patterns and identify major leverage points and
than national demand for many food items including opportunities to achievemultiple co-benefits of chan-
rice, the national staple, and fruits and vegetables—so ging diets among different population groups. There-
food supply is heavily supported through importation fore, we assessed deviation of the average Gam-
fromother countries [13, 14]. Ongoing economic and bian diet from the EAT-Lancet dietary guidelines for
demographic changes such as increased income and healthy and sustainable diets and identified lever-
high urbanisation rates have also shifted diets away age points to simultaneously improve nutritional and
from traditional foods that are high in wholegrain planetary health.
and vegetables towards more processed foods high in
refined grains, oils and sugar [15, 16]. These changes 2. Methods
have compounded health implications—increasing
overweight and obesity and diet related chronic dis- 2.1. Study design and survey details
eases (hypertension and diabetes) in adults [17, 18], This study analysed the Integrated Household Survey
and also reduce the resilience of diets by increas- (IHS2015/16) of The Gambia conducted between
ing dependence on food trade with associated high May 2015 and April 2016 [30, 31], The IHS2015/16
water [19] and carbon footprints [20]. Improving the was a comprehensive nationally representative cross-
food system to deliver healthy diets could therefore sectional survey with dietary data collected year-
be a means to improve health and increase envir- round to reflect seasonal changes in diets. The sur-
onmental sustainability [21]. But this will require vey was designed to enable comparison of average
realignment of the current food systems and con- diets at national and district level and to explore
sumption patterns—supported by strong political rural-urban differences. It covered data collection
will [22]. on demographic and economic household charac-
Drawing from the best available evidence, the teristics. Details of the sampling procedure used by
EAT-Lancet Commission in 2019 proposed a univer- the IHS2015/16 are provided elsewhere [30]. Briefly,
sal reference ‘diet for the Anthropocene’ to deliver the survey used a two-stage probability proportional
optimal human health whilst maintaining envir- to size procedure with stratified random sampling.
onmental sustainability [23]. The diet is estim- TheGambia Bureau of Statistics defined enumeration
ated to sustainably feed the future population and areas (EAs) across the eight local government areas
prevent a substantial number of deaths from diet (LGAs) (including two municipalities) and districts
related NCDs [23]. The diet is largely plant-based were selected at the first stage. Each EA was classified
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Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
as either rural or urban. The next stage involved food system, nutritional needs and eating patterns.
selection of an equal number of households with Method 1 scores consumption of food groups to
equal probability of selection from the household list- reflect on micronutrient adequacy [35]. The method
ing in each EA. Overall, 622 EAs and 13 340 house- assigns one point for intakes within the EAT-Lancet
holds were selected with a response rate of 99.4% range for each food group and zero points for con-
(13 281 households interviewed). sumption outside of the range. The method does
not assign positive scores for zero intakes of essen-
2.2. Dietary data and processing tial food groups. The ranges of intake recommended
The IHS2015/16 collected quantitative house- by EAT-Lancet often include zero intake values (e.g.
hold food consumption data using a 7 d recall 0–14 grams for beef and lamb and 0–14 grams for
questionnaire [31]. The questionnaire included 145 pork) to allow for interchangeability and replace-
food items organised into broad food groups: cereals ment between closely related food groups [23]. How-
and products; poultry and products; meat; fish; milk ever, in many food insecure or minimally food secure
and products; oils and fats; fruits; nuts; starchy roots areas, such as The Gambia, there is low availabil-
and tubers; vegetables; sugar, honey and confection- ity of alternatives to replace non-consumed food
ary; and spices and condiments [30]. Our analysis groups. Consequently, assigning positive scores for
includes consumption of 92 food items excluding non-consumption of these foods could be a proxy
spices and condiments (supplementary table S1). for inadequate intake of micronutrients [35]. In these
Quantities of consumption were reported in both instances, the mean of the target range is taken as the
metric units and household measures (e.g. one cup lower bound instead of zero [35]. We adopted this
of rice) which were converted into grams of aver- approach by Method 1 to ensure greater micronutri-
age household intake per person per day by dividing ent adequacy of the resulting index.
equally by number of people in households. Where The scoring approach used by Method 2 reflects
household measures were reported without metric risk of NCD and associated mortality [36] by assign-
unit equivalent estimation, we estimated the gram ing scores 0–3 depending on different levels of con-
equivalents usingmarket determined quantities (sup- sumption of food groups. The method assigns higher
plementary material S1). scores for greater consumption of ‘emphasised’ food
We calculated total energy intake by linking food groups forwhich high consumption is good for health
intake data with the United Nations Food and Agri- (vegetables, fruits, unsaturated oils, legumes, nuts,
culture Organization (FAO) food composition tables wholegrains, and fish) while points are taken away
for West Africa [32]. The US Department of Agricul- for higher consumption of ‘limited’ food groups for
ture’s food composition data [33] and Gambia spe- which overconsumption is bad for health (beef and
cific tables [34] were used where food items were not lamb, pork, poultry, eggs, dairy, potatoes, and added
contained in the West African tables. sugar) [36]. Method 2 does not make micronutri-
ent adequacy considerations for nutrient-rich food
2.3. Covariates groups including meat and dairy which may lead to
Most covariates were at household level unless diets rich in these food groups being penalised under
specified otherwise. The covariates considered for this scoring system.
multivariable regression modelling were: household In our combined EAT-Lancet index (SHDI), we
wealth; remittances per capita; seasonality; crop pro- used the points distribution system similar toMethod
duction diversity; total energy; sex of household 2 (0–3 points) and applied micronutrient adequacy
head; ethnicity; education of household head; house- considerations for nutrient-rich food groups similar
hold size; and urbanisation status (supplementary to Method 1. Therefore, in food groups where the
material S2). EAT-Lancet range includes zero intake as the lower
bound such as beef and lamb (0–14 grams) we used
2.4. The sustainable and healthy diet index (SHDI) the mean of the target range to represent the lower
score bound instead of zero (i.e. 7–14grams) (Method 1).
The EAT-Lancet reference diet corresponds to We then assigned the scores (0–3 points) according to
2500 kcal per day energy needs for a 30-year-old consumption within or outside this new range avoid-
woman weighing 60 kg with moderate to high phys- ing positive points for zero intake (table 1 and supple-
ical activity level. It sets serving averages and suitable mentary material S3). This avoids assigning a positive
ranges (in grams per person per day) for each food score for non-consumption of these food groups as
group to reflect diets associated with greater health would result from applying Method 2.
and environmental sustainability [23]. To measure Overall, 16 food groups (based on EAT-Lancet
adherence to, or deviations from, the proposed diet, recommendations with some modifications) were
we developed an EAT-Lancet diet index (the ‘sustain- defined in this study with each having a maximum
able and healthy diet index (SHDI)’) by combining score of three points depending on intake level—
two previous scoring methods [35, 36] (Method 1 resulting in a total maximum score of 48 for the com-
and Method 2 respectively) to reflect The Gambian posite SHDI. Further details about the scoring criteria
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Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
Table 1. Scoring system used to generate the SHDI.
EAT-Lancet target Intake range with Scoreb
EAT-Lancet food intake (range in minimum intake
group grams d−1) values (g d−1)a 3 2 1 0
All vegetables 300 (200–600) 200–600 >300 200–300 100–200 <100
All fruits 200 (100–300) 100–300 >200 100–200 50–100 <50
Unsaturated oils 40 (20–80) 20–80 >40 20–40 10–20 <10
Beans, lentils and peasc 75 (0–150) 75–150 >75 37.5–75 18.75–37.5 <18.75
Peanuts and tree nuts 50 (0–100) 50–100 >50 25–50 12.5–25 <12.5
Wholegrainsc 116 (0–232) 116–232 >116 58–116 29–58 <29
Potatoes and cassava 50 (0–100) 50–100 >50 25–50 12.5–25 <12.5
Fish 28 (0–100) 28–100 >28 14–28 7–14 <7
Palm oil 6.8 (0–6.8) ⩽6.8 <1.7 1.7–3.4 3.4–6.8 >6.8
Added sugar 31 (0–31) 15.5–31 <7.75 7.75–15.5 15.5–31 >31
Refined grainsc 116 (0–232) 116–232 <116 58–116 116–232 >232
Beef and lamb 7 (0–14) 7–14 7–14 3.5–7 1.75–3.5 <1.75 or >14
Pork 7 (0–14) 7–14 7–14 3.5–7 1.75–3.5 <1.75 or >14
Poultry 29 (0–58) 29–58 29–58 14.5–29 7.25–14.5 <7.25 or >58
Dairy 250 (0–500) 250–500 250–500 125–250 62.5–125 <62.5 or >500
Eggs 13 (0–25) 13–25 13–25 6.5–13 3.25–6.5 <3.25 or >25
a Based on Method 1 [35] except for refined grains and palm oil where we allowed positive scoring for non-consumption. Our approach
treats beef & lamb and pork as two groups and splits grains into wholegrains and refined grains.
b Scores were assigned based on Method 2 [36] with exceptions to: wholegrains, beef and lamb, pork, poultry, dairy, and potatoes and
cassava where we used different criteria and avoided awarding points for non-consumption. We awarded points differently for added
sugar intake by taking points away for intakes above the upper limit while Method 2 assigned positive scores for intakes up to 200% of
the upper limit.
c Grains (whole and refined), beans, lentils and peas are dry, raw and includes soy foods consistent with EAT-Lancet recommendations.
EAT-Lancet recommendations for grains are combined with target 232 g (0–464 g). These were split in this report to reflect local
availability and consumption patterns.
used for each food group and specific modifications (24.5%) and the West Coast region (22.2%), with the
applied to the SHDI are shown in table 1 and supple- smallest number of households reporting from Ban-
mentary material S3. jul (5.6%). More than two thirds of the households
were in rural areas (75.6%), 84.8% were headed by
2.5. Statistical analyses a male family member, and 76.1 of the households
Scores obtained for each food group were summed had a head without schooling. More than seven in
to form a composite SHDI. The proportion of total ten households reported to grow at least one crop
index scores over the total expected scores was used (77.4%) and approximately two in five households
as an indicator of the level of adherence to the EAT- received remittances during the last year (37.7%)
Lancet recommendations. We used both graphical (supplementary table S3).
methods and descriptive statistics to explore and
summarise the data and to elicit patterns. 3.1. Mean consumption of energy and food groups
We fitted multivariable mixed effects regression Average daily energy intake per capita was
models specifying ‘region’ as a random effect and 2536 kcal with wide regional variation. The lowest
other covariates as fixed effects using maximum- energy intake was recorded in West Coast region
likelihood estimation to assess factors associated with (2011.0 kcal day−1) while those in Central River
a 1-unit increase or decrease in the SHDI. Potential and Upper River regions had the highest energy
multicollinearity among variables was assessed using intake of 2912.9 kcal per person per day compared
the variance inflation factor by including the vari- to the 2500 kcal person day−1 recommended by EAT-
ables of the fully adjusted model in a normal least Lancet. Households in rural areas (2616.9 kcal per-
squares regression. All statistical analyses were per- son day−1) consumed more energy than their coun-
formed using Stata version 16.1 (StataCorp, USA). terparts in urban areas (2284.3 kcal person day−1).
There was 100 kcal more energy intake on aver-
3. Results age in the rainy season than in the dry season
(2512.6 kcal person day−1). Households headed
From an initial sample of 13 281, the current analysis by men also had higher energy intakes over female
includes 12 713 households after data processing to headed households (table 2 and supplementary table
exclude households reporting extreme energy intakes S4). Consumption of different food groups differed
(supplementary table S2). Proportional to the pop- by household and geographic characteristics. For
ulation distribution, the majority of the households example, consumption of fruit and vegetables was
in the sample were based in the Central River region high among household members in urban areas
4
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
5
Table 2. Background characteristics of sampled households, energy, and food group consumption.
Type of settlement Season mean Household head mean
Percent of households Mean consumption mean (95% CI) g day−1 (95% CI) g day−1 (95% CI) g day−1
EAT-Lancet consuming each food group of food groups
food group per day (national) % (95% CI) (national) g day−1 Urban Rural Rainy Dry Male Female
Total energy 2536.2 2284.3 2616.9 2616.1 2512.6 2545.6 2483.6
(2514.3–2558.2) (2247.3–2321.2) (2590.6–2643.2) (2568.4–2663.9) (2487.9–2537.3) (2521.4–2569.8) (2431.7–2535.5)
All vegetables 96.6 (96.0–97.0) 153.9 (151.5–156.3) 206.2 137.2 145.6 156.4 144.4 207.4
(200.7–211.7) (134.7–139.7) (140.7–150.6) (153.7–159.1) (141.9–146.8) (200.2–214.5)
All fruits 37.2 (36.3–38.0) 53.1 (50.7–55.6) 77.8 (72.0–83.6) 45.2 (42.7–47.7) 22.6 (20.3–24.9) 62.1 (59.2–65.1) 50.9 (48.4–53.4) 65.3 (58.3–72.4)
Unsaturated 87.2 (86.6–87.7) 21.8 (21.4–22.1) 24.0 (23.2–24.7) 21.1 (20.7 (21.4) 21.6 (20.9–22.4) 21.8 (21.4–22.2) 20.9 (20.6–21.3) 26.6 (25.6–27.6)
oils
Beans, lentils 26.5 (25.7–27.2) 8.6 (8.2–9.0) 5.1 (4.5–5.6) 9.7 (9.3–10.2) 8.8 (8.0–9.6) 8.5 (8.1–8.9) 8.9 (8.5–9.3) 6.7 (5.8–7.6)
and peas
Peanuts and 67.3 (66.5–68.1) 19.1 (18.4–19.7) 15.3 (14.1–16.6) 20.2 (19.5–20.9) 18.9 (17.5–20.3) 19.1 (18.4–19.8) 19.2 (18.6–19.9) 17.9 (16.3–19.5)
tree nuts
Wholegrain 19.8 (19.1–20.5) 41.7 (39.7–43.8) 6.7 (5.1–8.2) 53.0 (50.3–55.6) 51.1 (46.4–55.9) 39.0 (36.7–41.3) 47.0 (44.6–49.4) 12.4 (9.6–15.2)
Potatoes and 48.4 (47.5–49.5) 18.8 (18.3–19.4) 34.9 (33.3–36.4) 13.7 (13.2–14.3) 18.0 (16.8–19.3) 19.1 (18.4–19.7) 17.6 (17.0–18.2) 25.5 (23.8–27.3)
cassava
Fish 93.8 (93.4–94.2) 81.1 (79.9–82.3) 93.5 (90.7–96.4) 77.1 (75.8–78.5) 79.9 (77.3–82.6) 81.4 (80.0–82.8) 76.3 (75.1–77.6) 107.8
(103.9–111.6)
Palm oil 68.8 (68.0–69.6) 7.6 (7.4–7.7) 9.1 (8.7–9.4) 7.1 (6.9–7.3) 8.1 (7.7–8.4) 7.4 (7.3–7.6) 7.2 (7.1–7.4) 9.6 (9.1–10.1)
Added sugar 96.4 (96.1–96.7) 66.5 (65.6–67.5) 76.7 (74.4–79.0) 63.3 (62.3–64.3) 65.4 (63.4–67.4) 66.9 (65.8–67.9) 65.8 (64.8–66.8) 70.7 (68.2–73.2)
Refined 98.8 (98.6–99.0) 411.6 (407.0–416.1) 352.5 430.4 429.6 406.2 415.7 388.1
grains (345.8–359.3) (424.9–436.0) (419.9–439.4) (401.1–411.3) (410.7–420.8) (378.3–397.9)
Beef and 28.4 (27.7–29.2) 12.4 (11.8–12.9) 17.5 (16.1–18.8) 10.7 (10.2–11.2) 12.5 (11.4–13.6) 12.3 (11.7–12.9) 12.2 (11.6–12.8) 13.2 (11.9–14.5)
lamb
Poultry 26.8 (26.0–27.6) 12.3 (11.8–12.8) 18.6 (17.2–19.9) 10.3 (9.8–10.8) 12.3 (11.3–13.3) 12.3 (11.7–12.9) 11.5 (11.0–12.0) 17.0 (15.3–18.7)
Dairy 44.0 (43.2–44.9) 26.6 (25.5–27.7) 21.8 (20.0–23.6) 28.1 (26.8–29.4) 27.6 (25.3–29.9) 26.3 (25.0–27.5) 27.1 (25.9–28.4) 23.5 (20.9–26.0)
Eggs 13.8 (13.2–14.4) 1.3 (1.2–1.4) 3.2 (2.9–3.5) 0.7 (0.6–0.8) 1.4 (1.2–1.6) 1.3 (1.2–1.4 1.2 (1.1–1.3) 1.6 (1.4–1.9)
Pork is excluded from table as consumption⩽0.5 g day−1. CI: Confidence Interval
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
compared to rural areas, but households in urban in four or more food groups (these were mainly fish,
areas also consumed relatively higher amounts of palm oil, vegetables, and unsaturated oils) (figure 3
sugar, and beef and lamb. In contrast, total grain and supplementary table S6). However, households
intake was higher among rural households than that scored three points on only one food group also
urban households. Furthermore, the intake of fruits, scored two points on a number of other food groups
vegetables, and grains (whole and refined) varied for which consumption did not reach a three score
more by season than other food groups. While fruit (supplementary table S6).
and vegetable consumption was higher in the dry
season compared to the rainy season, the reverse was 3.3. Determinants of increased sustainable and
true for consumption of grains (table 2 and supple- healthy diet index (SHDI) score
mentary table S4). The adjusted mixed effects model (accounting for
per capita energy intake and receipt of remittances)
3.2. Household food consumption and adherence showed that diets of female headed households scored
to EAT-Lancet diet recommendations 0.32 points higher on the SHDI than diets of male
Comparing mean intakes to the EAT-Lancet tar- headed households (95% CI: 0.14–0.50, P < 0.001).
gets, only a small proportion of household members Similarly, diets of households in urban areas scored
had intakes falling within the recommended range 0.61 points higher compared to those in rural areas
(figure 1). Food groups with a relatively high propor- (95% CI: 0.41–0.81, P < 0.001). There was a posit-
tion of households consuming within the EAT-Lancet ive association between household wealth index and
target include: fish (50.5%) and unsaturated oils the SHDI (β = 0.37; 95% CI: 0.32–0.43, P < 0.001).
(40.8%)—all other food groups had a quarter or less Furthermore, in households where the head had no
of households with consumption falling within the schooling, there was a lower mean dietary index score
EAT-Lancet range. The majority of household mem- (β=−0.41; 95%CI:−0.57-(−0.26), P < 0.001) com-
bers had mean intakes above the upper limit recom- pared to households where the head received some
mended by EAT-Lancet for added sugar (77.5%), schooling. There was evidence of a strong relation-
refined grains (76.1%), and palm oil (43.9%). For ship between ethnic group and dietary index score:
all other food groups (fruits, vegetables, pork, beef compared to Mandinkas, other ethnicities (Fula, Jola
and lamb, eggs, dairy, poultry, potatoes and cassava, and Serahulleh) showed lower index scores, except
wholegrains and peanuts and tree nuts), most house- the Wollof who scored higher (table 3). Diets in the
holds consumed below the lower range (figure 1). dry season scored on average 0.47 points higher on
However, more than 20% of households were also the index than those in the rainy season (95% CI:
consuming above the upper range for beef and lamb 0.32–0.61, P < 0.001). Crop production diversity was
and fish. Consumption above the recommendation also positively associated with the SHDI (β = 0.14;
for beef and lamb and fish was higher among the 95% CI: 0.10–0.19, P < 0.001) while each addi-
wealthiest households and those residing in urban tional family member was associated with a mar-
areas (supplementary table S5). ginal decrease in dietary score of 0.02 points (−0.04-
Consequently, the overall score on the SHDI was (−0.01), P < 0.001) (table 3).
very low, with a mean composite index of 10.1/48
(SD = 3.7) and a highest reported score of 28.0/48 4. Discussion
(supplementary figure S1). The distribution of SHDI
scores obtained by households for each food group is 4.1. Main findings
presented in figure 2. Note that failure to meet targets In this study, we have demonstrated that aver-
for any individual category does not imply an overall age Gambian diets typically show strong deviations
failure because substitutions are permitted. from the healthy and sustainable dietary guidelines
Considering adherence by individual food groups as proposed by the EAT-Lancet Commission. The
and consistent with figure 1, most households (79%) diet was dominated by consumption of less-healthy
scored three points for fish intake. The proportion of options such as refined grains and added sugars
households scoring three points for other food groups which exceeded the recommendations, whilst intake
was lower than 50%. For refined grains, most house- of nutritionally important food groups such as fruits,
holds (76%) scored zero points due to over consump- vegetables, dairy, and poultry were much lower than
tion, but most households (84%) scored zero points the EAT-Lancet targets. Less than a third of the pop-
onwholegrain intake due to extremeunder consump- ulation consumed beef and lamb, with many non-
tion. Many households (>70%) also reported very or very low consumers with low wealth indices and
low or no consumption of fruits, beans, lentils and living in rural areas while there were some over-
peas, beef and lamb, dairy, pork, eggs, and chicken, consumers of these foods in the wealthiest and urban
resulting in scoring zero points in these food groups households. Relatively highmeat intake among urban
(figure 2). Overall, 66.8% of households scored three dwellers is consistent with the wider sub-Saharan
points in one or two food groups (comprising mainly Africa region [37]. Importantly, we show that, con-
fish and palm oil) and only 10% scored three points sistent with similar low-and middle-income settings
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Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
Figure 1. Comparison of mean household food group consumption with EAT-Lancet ranges [Recommended ranges are
according to Method 1 with minimum values as described in the ‘intake range’ column of table 1].
[38], the diet does not fulfil nutritional requirements consumed (e.g. polished white rice, bread, oils, and
but consumption is often within recommended levels added sugar) while others are under consumed; both
for food components known to impact heavily on the cases result in deviations from the EAT-Lancet targets.
environment (such as livestock products) [21]. We The higher scores on the SHDI in the dry sea-
also identified important socioeconomic character- son compared to the rainy season are consistent with
istics that could serve as leverage points for improving results from Kenya and Vietnam [35]. As other food
healthiness whilst not impacting on the sustainability groups remained relatively unchanged throughout
of diets in The Gambia. the year, higher availability of fruit and vegetables
during the dry season as compared to the rainy sea-
4.2. Research in context son explains much of the difference in scores. High
Diets in The Gambia typically show low dietary SHDI scores among those with better wealth, school-
diversity [39], which partly explains the low levels ing and urban settlement also seem to be driven by
of alignment with the healthy and sustainable diet- availability and consumption of fruits and vegetables.
ary guidelines by the EAT-Lancet Commission. A less Furthermore, female-headed households have been
diverse diet implies that a few food groups are over shown by past studies to spend a higher proportion
7
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
Figure 2. Distribution of scores obtained on each of the 16 food groups [Scores 1, 2 and 3 generally refer to consumption within
acceptable limits of a food group. A 0 score generally means consumption outside acceptable limits for a food group (details in
table 1). Scores 0, 1, 2 & 3 are shown by light shades of red, orange, blue and green respectively. Scores with 0% households are
not shown].
Figure 3. Percent of households meeting the EAT-Lancet guidelines by number of food groups [Total number of food
groups= 16. Meeting guidelines here is defined by obtaining a score of 3 in each food group].
of income towards household food and nutrition (in the positive association between SHDI and home
this case, on more vegetables) than males [40]. This agricultural production found in this study. Con-
underscores the overarching importance of fruit and trary to a recent meta-regression that found higher
vegetables in improving diets and meeting healthy vegetables intake in rural areas as compared to urban
and sustainable diet targets in The Gambia. Previous areas [37], urban residence could be a good proxy
evidence shows that increased production diversity is for better access to food markets and income than in
associated with diet diversity [41], which may explain rural areas and may explain the higher SHDI scores
8
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
Table 3.Mixed effects regression analysis of the determinants of EAT-Lancet diet index in The Gambia.
EAT-Lancet index score (β)
(95% confidence interval)a P-value
Household head <0.001
Male 0 (base)
Female 0.32 (0.14–0.50)
Area of residence <0.001
Rural 0 (base)
Urban 0.61 (0.42–0.81)
Wealth quintile 0.37 (0.32–0.43) <0.001
Ethnicity/tribe <0.001
Mandinka/Jahanka 0 (base)
Fula/Tubular/Lorobo −0.31 (−0.47− (−0.15))
Wolof 0.37 (0.17–0.58)
Jola/Karoninka −0.02 (−0.29–0.25)
Serahulleh −0.01 (−0.30–0.28)
Other −0.07 (−0.36–0.22)
Household head ever <0.001
attended school
Yes 0 (base)
No −0.41 (−0.57− (−0.26))
Season <0.001
Rainy 0 (base)
Dry 0.48 (0.32–0.61)
Crop diversity score 0.14 (0.10–0.19) <0.001
Remittances (per capita) 9.17× 10−6 (1.58× 10−6−1.67× 10−5)b 0.02
Household size −0.02 (−0.04-(−0.01)) 0.001
Total energy 9.24× 10−4 (8.71× 10−4−9.77× 10−4)b <0.001
a Coefficients are adjusted for all other variables in the model.
b e= x10 exponentiation.
associated with urban settlement in this study [42]. increase to improve the nutrient content of the diet.
Finally, while remittances are a key source of house- These changes would involve a careful consideration
hold income in The Gambia [43] and linked with of the food supply and demand side dynamics.
improvement in food and nutrition security in sub- Improving food choice and demand can drive food
Saharan Africa [44], they were only weakly associ- supply under favorable structural factors that enable
ated with the sustainable diet index in this study. This adequate supply from both domestic production and
could be due to using income from remittances to buy import sources [45]. However, a variety of other
less healthy food groups (such as refined grains and factors that influence food choice would need to be
sugar) or for purchases of non-food household items. tackled—including the affordability of food groups
that are currently under-consumed, nutrition educa-
4.3. Implications including policy tion about the importance of dietary diversity, food
recommendations preferences, and marketing practices [46].
If The Gambia was to successfully promote healthy In many low- and middle income countries, one
and sustainable dietary guidelines, such as those of the main barriers to consuming the recommen-
proposed by the EAT-Lancet commission, it would ded amount of fruit and vegetables as per the EAT-
require substantial shifts in current food supply Lancet recommendations is their affordability [47]. In
and consumption patterns. Chiefly, it would involve addition to high cost, the supply of fruit and veget-
increasing the supply and intake of fruits, vegetables ables from both domestic production and imports
and wholegrains as well as ensuring that they are fromother countries is often insufficient: in the Gam-
available in all parts of the country throughout the bia, average per capita fruit and vegetable supply falls
year. This would have to go along with cutting down short of national demand [48, 49], and would need to
on refined grains (polished white rice and bread) be doubled/tripled (especially for fruits) to meet the
and added sugar. Also, the current low amounts of EAT-Lancet recommendations. This trend is notice-
livestock products with a dominant aquatic source able in other low- and middle-income settings. For
of protein (mainly fish) would need to be main- example, in India, an additional US $1.0 was required
tained to remain within health and sustainability lim- per household member per day in order to purchase
its. The national average intake of dairy products lies the amount of fruit and vegetables (as well as other
far below the 250 g EAT-Lancet target and needs to food groups) recommended in the EAT-Lancet diet
9
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
[50]. High price volatility of fruit and vegetables in Currently average beef and lamb consumption
different seasons further complicated the affordability is low or zero for the majority of the population,
question [50]. while a smaller proportion of (mostly) urban dwell-
Given the clear discrepancy between current sup- ers have higher intake than recommended by the
ply and fruit and vegetable supply required for EAT-Lancet diet. In the Global North red meat is
population-wide shifts to healthy and sustainable grossly overconsumed by many and serves as a major
dietary guidelines in The Gambia, adequate action to source of food system emissions—the relatively small
improve supply streams would be crucial. This could amounts of red meat consumption as recommen-
involve various pathways including investments by ded by sustainable and healthy dietary guidelines
government and development partners to increase often mean a substantial cut in meat consumption
the supply of fruits and vegetables, but also methods for the majority of people in the Global North if
to overcome seasonal variability in supply, such as they wish to adhere to such guidelines. In The Gam-
preservation methods and introduction of early and bia, this is however more complex: given the double
late cropping varieties. burden of malnutrition, low dietary diversity and
The Gambia relies heavily on imported refined the relatively low environmental impact of agricul-
grains as the major staple foods [51] likely due to ture (including that of livestock—kept extensively
their relative low prices, high convenience for cook- and fedmainly on low-opportunity cost biomass such
ing and eating, and prestige associated especially with as grass with lower environmental impact compared
consumption of rice compared to alternative grains to those kept intensively and fed with cereals [57]),
[52]. For alternative and more healthy wholegrains blanket meat reduction strategies are less of a use-
to gain dominance over refined rice in The Gam- ful option to improve healthfulness and sustainabil-
bia, the factors that make rice attractive will need to ity in the immediate term. In fact, for the majority
be equalised. Promoting wholegrain alternatives such of the Gambian (rural) population the small amount
as pearl millet and maize to reduce reliance on rice of red meat as recommended in healthy and sustain-
and refined wheat bread could have multiple bene- able dietary guidelines would in fact translate into
fits: higher consumption of wholegrains would likely an increase in red meat consumption as compared
impact positively on both health and the environ- to their current diets. Therefore, a more targeted
ment. For instance, millet production is associated approach to nutrition education is required to facilit-
with lower greenhouse gas emissions compared to ate changes in red meat consumption patterns across
rice [53] and it can easily be eaten as wholegrain com- different population groups that are appropriate to
pared to rice that is almost always refined. In addition, need.
millets are relatively more adaptable to the local cli- Cutting down on the amount of added sugar in
mate than rice as millet has been grown traditionally the Gambian diet will improve diet quality. Until
over decades in The Gambia [54]. There are further 2011, the Gambian government provided tax waivers
advantages for promoting millet as an alternative to on imported sugar [58]. In spite of the removal of tax
rice because it is already the second most consumed exemptions, Food Balance Sheet data from the FAO
grain in the country (especially in rural areas) and show that daily sugar supply in Gambia has contin-
has multiple local recipes [51]. The low consump- ued to increase (from 83 g person day−1 in 2011 to
tion of millet is largely the result of inadequate sup- 99 g person day−1 in 2019) [59]. This may imply that
ply and low convenience in its processing and pre- sugar is still cheaper than the minimum threshold
paration which limits uptake especially among busy required to reduce demand. Possible strategies to
urban dwellers—this needs to be addressed to enable reduce sugar consumption may involve a combin-
nationwide scale-up. ation of approaches with complementary effects
Locally sourced fish is the main source of animal including taxation, food based dietary guidelines and
protein in the diet together with low amounts of social behaviour change communication.
poultry and livestock products in The Gambia.
Although this combination is often estimated to 4.4. Strengths and limitations
ensure environmental sustainability [21], possible This study has several strengths. First, we used
overexploitation of local fish stocks by foreign fish- a national sample with multiple variables which
meal factories [55] greatly threatens the sustainab- allowed examination of diets at sub-national and
ility and long term resilience of fish supply for the household levels. The design of the survey also
future [56]. This is particularly relevant as fish is often allowed us to assess diets in different seasons of the
the only nutrient-rich food consumed in adequate year for a more comprehensive understanding of the
amounts by those with less diverse diets. Hence a national diet. Our scoring system has also allowed a
declining supply (and potential price increase) would good understanding of the extent of deviation and
make fish inaccessible and/or unaffordable in this conformity of different food groups to the EAT-
group, which could disproportionally disadvantage Lancet diet targets and to identify leverage points for
them—reducing diet quality. improvement.
10
Environ. Res. Lett. 17 (2022) 104043 Z Ali et al
However, the study also has several limitations. Data availability statement
We estimated an average household intake per person
and compared this to a reference diet. This did The Integrated Household Survey 2015/16 data
not allow us to explore potential non-equitable analysed in this study are publicly available from
food distribution among household members (for the World Bank (https://microdata.worldbank.org/
example, children may be consuming less energy index.php/catalog/3323).
overall but they may also eat more seasonal fruits
than adults) [60]. There was also a possibility for bias Acknowledgments
by comparing average intakes to a standard reference
diet. For example, rural andmore farming dominated This study was developed as part of the Food sys-
households may be more physically active than urban tem Adaptation in Changing Environments in Africa
dwellers, by comparing to the standard reference diet (FACE-Africa) project, aWellcome Trust funded pro-
this likely introduced a bias in which overconsump- ject (Grant No. 216021/Z/19/Z) under the Wellcome
tion by urban dwellers is underestimated and under- Climate Change andHealth Award Scheme.We thank
consumption by rural dwellers is underestimated. the two anonymous reviewers who helped to improve
The 7 d food frequency questionnairemethod of diet- the study.
ary intake assessment is vulnerable to recall prob-
lems but is more likely to reflect the ‘regular diet pat- Conflict of interest
tern’ of households than shorter recall periods such
as 24 h recalls. Additionally, the EAT-Lancet diet tar- None declared.
gets are more focused on adults [23] and may not
apply directly to nutritionally vulnerable groups such Ethics statement
as young children or pregnant and lactating women
[61]. Furthermore, the EAT-Lancet diet ismore plant- Ethics approval for this study was provided by The
based, implying a dominant plant-source iron sup- Gambia Government/MRC Joint Ethics Committee
ply which is less bioavailable as compared to haem- (reference: 21275).
based sources [62]. Therefore, for the diet to provide
optimal iron nutrition and reduce existing high levels Patient consent for publication
of iron deficiency and anaemia in the population
[61], promotion of the EAT-Lancet diet in this set- Not applicable
ting needs to particularly emphasise adequate supply
and consumption of appropriate amounts of livestock ORCID iDs
products (rich source of bioavailable iron and also
enhance absorption of plant source iron) as well as Zakari Ali https://orcid.org/0000-0002-8129-2230
fruit and vegetables (high in vitamin C to aid absorp- Pauline F D Scheelbeek https://orcid.org/0000-
tion of plant-source iron [63]). Our assessment of 0002-6209-2284
an average diet limited our ability to identify specific Alcade C Segnon https://orcid.org/0000-0001-
food group combinations that may exist within pop- 9751-120X
ulation sub-groups that are often identified through
dietary pattern analysis [64]. However, the use of References
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