Change in cost and affordability of a typical and nutritionally adequate diet among socio-economic groups in rural Nepal after the 2008 food price crisis
Change in cost and affordability of a typical and nutritionally adequate diet among socio-economic groups in rural Nepal after the 2008 food price crisis
Nasima Akhter 0 1 2 3
Naomi Saville 0 1 2 3
Bhim Shrestha 0 1 2 3
Dharma S. Manandhar 0 1 2 3
David Osrin 0 1 2 3
Anthony Costello 0 1 2 3
Andrew Seal 0 1 2 3
0 Wolfson Research Institute for Health and Wellbeing , Wolfson Building , Durham University Queen's Campus, University Boulevard, Stockton on Tees , Thornaby TS17 6BH , UK
1 UCL Institute for Global Health , 30 Guilford Street, London WC1N 1EH , UK
2 Abbreviations CoD Cost of Diet HEA Household Economy Approach HSS Household Surveillance System VDC Village Development Committee
3 Mother and Infant Research Activities, YB Bhawan , Thapathali, Kathmandu 921 , Nepal
Diet quality is an important determinant of nutrition and food security and access can be constrained by changes in food prices and affordability. Poverty, malnutrition, and food insecurity are high in Nepal and may have been aggravated by the 2008 food price crisis. To assess the potential impact of the food price crisis on the affordability of a nutritionally adequate diet in the rural plains of Nepal, data on consumption patterns and local food prices were used to construct typical food baskets, consumed by four different wealth groups in Dhanusha district in 2005 and 2008. A modelled diet designed to meet household requirements for energy and essential nutrients at minimum cost, was also constructed using the 'Cost of Diet' linear programming tool, developed by Save the Children. Between 2005 and 2008, the cost of the four typical food baskets increased by 19% - 26% and the cost of the nutritionally adequate modelled diet increased by 28%. Typical food baskets of all wealth groups were low in macro and micronutrients. Income data for the four wealth groups in 2005 and 2008 were used to assess diet affordability. The nutritionally adequate diet was not affordable for poorer households in both 2005 and 2008. Due to an increase in household income levels, the affordability scenario did not deteriorate further in 2008. Poverty constrained access to nutritionally adequate diets for rural households in Dhanusha, even before the 2008 food price crisis. Despite increased income in 2008, households remain financially unable to meet their nutritional requirements.
Food price crisis; Nutritionally Adequate Diet; Typical food basket; Poverty; Food security; Malnutrition
Although progress has been made in reducing hunger, about
795 million people are still undernourished globally, of whom
about 780 million live in developing countries and are unable
to access enough food for an active and healthy life
and Agriculture Organisation 2015)
. Diet quality is an
important determinant of the food and nutrition security of a
population and is influenced by food availability, access,
utilisation and affordability at both country and household
level. Since food cost is the most important determinant of
food purchasing decisions
(Lo et al. 2009)
, a food price rise
can exacerbate food insecurity and increase the risk of
(Martin-Prevel et al. 2012)
. Low diet quality is
often associated with poor socio-economic status (SES).
Monsivais et al. (2012)
observed that the differential
amounts spent among households of different
socioeconomic backgrounds explained the variable quality of
diet. Similarly, a modelling study of diets for French adults
found that imposing cost constraints led to a diet plan lower
in vitamin C and β–carotene than that of the average
(Darmon et al. 2002)
. Food prices and income
determine purchasing power and the affordability of healthier
(Drewnowski and Darmon 2005; Darmon and
and may suggest how resilient or
vulnerable households can be in responding to a food price
crisis. However, the relationship between food price and
income is not always predictable, as the larger food
environment, i.e. availability, convenience, and desirability of
foods in a certain location, can also play important roles
(Herforth and Ahmed 2015)
. It is therefore important to
understand and examine the impact of food prices in a given
The 2008 food price crisis increased the susceptibility of
many vulnerable households to malnutrition, but the effect
may have varied around the world due to many factors,
including regional variability in price rises, household income
levels, consumption patterns, and preferences for available
(Levine 2012; Mahajan et al. 2015)
. The World
Bank estimated that, globally, food price increases caused an
extra 44 million people to be undernourished and 100 million
people to fall into poverty (World Bank 2008). Price rises
affected the nutritional quality of diets, especially for the
lowest income countries and poorer socio-economic groups
within a country (Green et al. 2013;
Anríquez et al. 2013
et al. 2015). One reason for this is that the prices of
nutrientdense food items rose disproportionately and access to higher
quality nutritious foods became more restricted among poorer
households. Analysis of national level data may mask these
differences. In Seattle, USA, the trend in food prices between
2004 and 2008 showed that when foods were grouped by their
nutrient density, inflation for the highest quintile was nearly
double that of the lowest
(Monsivais et al. 2010)
. In Ghana,
the national impact of the 2008 global food price crisis was
moderate. However, impact varied by region due to
differences in consumption practices and income levels. Poorer
households in urban areas who bought most of their food,
and those who lived in northern Ghana and spent a large
proportion of their income on food, were the worst affected
(Cudjoe et al. 2010). Correct assessment of the nutritional
impact of a crisis can be difficult, as there is often a lack of
geographically detailed price data and methodologically
(Benson et al. 2013; Gibson 2013)
. To guide
program planning and suggest appropriate policy responses in
a local context, it is important to understand the extent of local
food price inflation and the heterogeneity of the population
impacts (Mahajan et al. 2015).
Various measurement tools have been used to understand the
differential impact of food prices on food security and nutrition
in different regions and among households with varying
(Anríquez et al. 2013; Green et al. 2013; Akter
and Basher 2014)
. Economic analysis has been done to
measure how the demand for different food groups responds to
changes in price (Green et al. 2013). Some studies have focused
only on staple prices, whereas price changes could vary for
different food groups, and this needs to be considered in
assessing the potential nutritional impact of changes in
(Nordström and Thunström 2011)
. A food price
index based on the prices of items in a typical food basket from
a country or region can be used to estimate food price inflation
and indicate the magnitude of loss of household purchasing
. Using data from 35 countries, the
World Food Programme estimated that, on average, the cost
of a food basket increased by 36% between 2007 and 2008
(Brinkman et al. 2010)
. In this WFP study, the cost of a food
basket in Nepal (for rural and urban areas combined) increased
by 19% over one year between 2007 and 2008. However, the
study did not assess whether household income had changed or
food substitution had occurred.
A food price index typically only takes into account the
energy sufficiency of the food basket, rather than its full
nutritional adequacy. It is generally made at country or regional
level and does not account for household-level
socio-economic differences. In addition, a change in food prices needs to be
examined in relation to change in income levels to assess
potential effects on different groups
(Mahajan et al. 2015)
The importance of income data was apparent from an analysis
in Sri Lanka, which found a 55% increase in food prices, a
26% increase in price of non-food items, but a 57% increase in
income between 2007 and 2009. The undernourished
proportion of the population was expected to increase by 1.7%, but
the predicted increase was much higher when changes in
income were not taken into account
(Korale-Gedara et al. 2012)
Estimation of the cost of a nutritionally adequate diet using
linear programming and household income levels can help
model the impact of a food price rise on the affordability of a
nutritionally adequate diet and thereby indicate its potential
nutritional impact. In several countries, linear programming
has been used to plan and estimate the cost of a nutritionally
adequate diet for children, men, and women
(Briend et al. 2001;
Darmon et al. 2002, 2006; Rambeloson et al. 2008; Dibari et al.
. The ‘Cost of Diet (CoD)’ tool was developed by Save
the Children to help design diets for the whole household
the Children UK 2011)
. The tool can be used to estimate the
cost and affordability of a household diet, which can be helpful
in understanding the potential for a localized nutritional impact
of a crisis among households with different socio-economic
(Save the Children UK 2009a)
. Several recent
studies have used CoD
(Save the Children UK 2009a, b;
Frega et al. 2012; Baldi et al. 2013; Save the Children
UK 2013a; Geniez et al. 2014; Termote et al. 2014; Biehl
et al. 2016)
, reflecting that it can be used as an advocacy
tool to promote food-based interventions or social safety
net programmes, depending on the specific context.
In this study, we used local market price data from the rural
plains of Nepal before and during the global food price crisis,
to estimate the cost, affordability, and nutritional content of
typical food baskets (TFB) and a modelled, minimum-cost,
nutritionally adequate diet (NAD). The unique features of this
study are that, rather than using country or regional level food
baskets, we calculated food price inflation based on a local
food price index and utilised consumption pattern and income
estimates from the area to plan the TFB as well as the
modelled NAD. These analyses, although they do not
compare regions, are important for Nepal as
Shively et al.
found that the relationship between environmental
conditions and nutritional status of children varied in different
regions. Furthermore, these analyses of impact of price rise on
affordability scenarios for the two methods (TFB and NAD)
were disaggregated by SES groups, which enabled our study
to examine the hypothesis that after adjusting for changes in
income, the potential dietary impact of the 2008 global food
price crisis would vary by socio-economic group.
Nepal is a diverse country with varied geography, topography,
and related agricultural and consumption practices. It has three
ecological zones: Hills, Mountains, and Plains. The Plains
occupy the smallest area but have the largest population. The
study was conducted in Dhanusha district, which lies in the
Plains bordering India and has an area of 1180 Sq. Km
(Central Bureau of Statistics 2008)
. It ranks 43rd out of 75
Districts on the Human Development Index
The study categorized the population of Dhanusha into
four socio-economic groups (wealth groups) and determined
a Typical Food Basket (TFB) for each group, which is detailed
in later sections. The TFB included a fixed set of food items
and met the energy (kcal) requirements of household
members. A minimum-cost, Nutritionally Adequate Diet (NAD)
that met the requirements for energy and key nutrients for
households in all wealth groups was also formulated using
linear programming. We estimated the cost of the TFB and
NAD and assessed the affordability for each wealth group,
before and after the 2008 global food price crisis.
2.1 Data sources and analysis
We combined data collected in Dhanusha, during several
studies, by enumerators from Mother and Infant Research
Activities (MIRA), a non-governmental organization. These
were a household economy approach (HEA) study, data from
a household surveillance system (HSS) study, a survey of
market prices, and a survey of change in income by sources.
Informed consent was obtained from all individual
participants included in the study.
Initial data were collected during March–June 2006 in 60
administrative units, called Village Development Committees
(VDC) in Dhanusha, using the HEA method introduced by
Save the Children UK
(Holzmann et al. 2008)
. The HEA uses
participatory group interviews to assess food security and the
actual or predicted impact of a livelihood shock in an area. The
HEA data from Dhanusha provided a description of the
characteristics of wealth groups (Very poor, Poor, Middle,
Betteroff) and their distribution within each of the 60 VDC. It
described their livelihoods and food security patterns, including
the annual consumption of food items and income and
expenditure by source for the year 2005
. The HEA
provided useful data on sources of income and the estimated
proportion of cash of food-derived income for each wealth
group, but quantification of average income varied and was
less reliable. Hence, median expenditure data was determined
and considered a reliable proxy estimate for income for each
wealth group (Table 1).
Baseline data (mid-September 2006 to mid-April 2007)
from a household surveillance system (HSS), on household
assets, housing characteristics, and primary sources of staple
food (Table 2) were analysed using principal components
analysis to create a SES index and rank households from the
same 60 VDC. In each of the VDC, the proportion of
households estimated to belong in each wealth group was available
from HEA data and used to group the ranked households into
‘Very Poor’, ‘Poor’, ‘Middle’, and ‘Better-off’ wealth groups,
in each VDC so that the SES characteristics of the wealth
groups could be described.
In 2008, we collected data on changes in income levels.
Firstly, HEA data were used to create income profiles for each
wealth group, which detailed their sources of income (e.g.
income from daily labour, factory work, self-employment
such as in a grocery shop, salaried workers, and seasonal
migratory work within Nepal and abroad, and Government
staff salaries). These were used as a basis for calculating
income change. Key informants who were engaged in
cashincome activities such as. daily waged labour and
selfemployment were identified by wealth groups and
interviewed about current (2008) and recalled (2005) income
. Using income profiles, data were
collected from all VDCs for change in income for the commonly
used income categories (e.g. agricultural labour daily pay: n =
60, one per VDC; seasonal migratory income: total n = 55;
overseas income from Arab countries: n = 57; Malaysia =
59). Other income data were collected through two key
informant interviews per six MIRA unit offices, i.e. maximum of
12 interviews/ income category (e.g. earnings from
selfemployment such as a snack shop = 10, medicine shop = 11).
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The monthly salaries of government employees were
collected from the District Development Committee office, District
Public Health Office and District Education office. The
income data was used to calculate the percentage change in
income between the two periods, and the change was then
used to estimate 2008 income levels. Using median total
expenditure as a proxy for income in 2005, we modelled 2008
income data as:
Cash income ¼ ð2005 cash incomeÞ þ ½ð2005 cash incomeÞ %change in cash income
Food derived income ¼ ð2005 food derived incomeÞ þ hð2005 food derived incomeÞX food
price inflation between 2005 and 2008i
More details of the 2008 income change data collection are
included in Appendix 5.
HSS data were collected on the consumption of food groups
(cereals, roots and tubers, green and other vegetables, fruits,
dairy, fish, meat, eggs, pulses and nuts, sugar and honey, and
others, such as spices, tea, or coffee) in the last 24 h were
summarised and used to define the dietary intake pattern for
each wealth group
. Food price inflation was
estimated using price data collected from retail vendors in the
most accessible market in each VDC, in 2005 and 2008
(SepOct). Data were collected from the same VDC markets in both
years. Allowing for changes (e.g. closure of markets) between
2005 and 2008, food prices from 48 VDCs (one market / VDC)
were utilised. Our study did not adjust for possible difference
between farm-gate prices and local market prices, but assumed
that since data were collected from the most accessible local
markets the differences would not be large. Details of this
estimation method are presented elsewhere
Data management and analyses were done in the Statistical
Package for the Social Sciences (SPSS), version 16.0
(Statistical Package for the Social Sciences 2007)
, except for
linear programming analysis, which was performed using the
(Save the Children 2011; Save the Children
run using the Solver add-in function in MS-Excel 2003
(Excel 2003). Details of data collection and management are
2.2 Calculation of parameters used for Typical Food
Baskets (TFBs) and Nutritionally Adequate Diet (NAD)
Mean food prices For both 2005 and 2008, after excluding
outliers that were either < Q1–1.5*IQR or > Q3 + 1.5*IQR
(where Q1 = lower quartile; Q3 = Upper quartile; IQR = Inter
(UK Office for National Statistics 2007)
mean prices of food for each 100 g of purchased item (Web
Table 1) were used to estimate the cost of TFB and NAD.
Median household expenditure Using HEA data, annual
household expenditures by wealth group for 2005 were
estimated. Median expenditure levels served as a proxy for
income (Akhter 2013).
Income level for wealth groups in 2008 The income levels of
wealth groups in 2008 were estimated using 2005 expenditure
as the base and incorporating changes in income between
2005 and 2008. Details of these calculations are mentioned
Food composition Tables A food composition database for 64
commonly available items in Dhanusha was prepared using
the USDA National Nutrient database
(U.S. Department of
, the East Asia Food Composition database
(Food and Agriculture Organisation 1972) and the
Bangladeshi food composition tables
. These food
values were inputted into the Cost of Diet (CoD) database
(Save the Children UK 2011)
and were also used for
estimation of the food energy (kcal) in the TFB.
Household demographics and energy requirements The
demographics of a model household, and the energy and nutrient
requirements of its members were estimated on the basis of
primary data and relevant findings from national and regional
studies (Hirai et al. 1993; Food and Agriculture Organisation
2010; Ministry of Health and Population (MoHP) 2012).
Firstly, based on our HEA findings a model household was
defined as including six members: 2 boys (aged 2–3 and 5–
6 years), 1 adolescent girl of 13–14, and 3 adults (1 male aged
37, 1 female aged 28, and 1 female aged 45–50)
. Secondly, the energy requirements of household
members were set based on FAO standards and available evidence
about physical activity levels (PAL) for Nepal
(Sudo et al.
2006; Food and Agriculture Organisation 2004a)
. For the
children a nd adolescents, habitual activi ty levels
recommended by the Food and Agriculture Organisation
(2004a) were used. Both adult men and women aged 20–44
were considered to be moderately active
Agriculture Organisation 2004a; Sudo et al. 2006; Central
Bureau of Statistics 2008)
. The senior woman in the household,
aged 45–50, was considered to be lightly active (Akhter 2013).
The PAL and corresponding energy requirements of the
household members for both TFB and NAD were calculated
using guidelines developed by the joint FAO/WHO/UNU
Expert Consultation in 2001
(Food and Agriculture
. In addition, the CoD program used
inbuilt requirements set for macro- and micronutrients specific
for age, sex, and pregnancy or lactation
(Save the Children
; (Frega et al. 2012).
The same six members and their age, sex, physiological
status, and activity levels were used in the calculation of
TFB and NAD. Because there was a paucity of data on
whether body size or PAL varied in rural Nepal by wealth status, for
the purposes of the analysis we assumed that the energy
requirements of households did not vary by wealth group. We
considered that, although members of a wealthier household
would be heavier than members of a poorer household, the
PAL would be lower for wealthier than for poorer households
and the energy needs were therefore likely to be
approximately equal across wealth groups.
2.3 Estimating the cost of household Typical Food
To estimate the cost of a TFB, a daily food basket for an adult
male was planned and costed for each wealth group. The
weight of each food group to be included was first estimated
for the combined wealth groups using data from another study
(Hirai et al. 1993)
. Secondly, this food basket was then
adjusted to create 4 wealth group specific food baskets using our
HSS 24-h data on food group consumption (Table 3). Thirdly,
for each wealth group, the most frequently consumed item/s in
a food group (based on HEA data) was selected for inclusion
. The energy content of the included food items
met the requirement for an adult male.
Finally, to estimate the cost of the household TFB, the cost
of the food basket for the one adult male was calculated using
market price data. This cost (in Nepalese Rupees, per kcal),
was then multiplied by the total energy requirement for all
household members to give the cost of the household TFB.
This process was repeated for each wealth group. The 2005
and 2008 TFB included the same set of food items.
2.4 Modelling a minimum-cost, nutritionally adequate diet (NAD)
The Cost of Diet (CoD) tool was run to select the foods and
the amount of each food that would meet household
requirements for energy (kcal) and nutrients with the objective
function set to minimize cost. The CoD generated the lowest cost
diet plan for the household that was nutritionally adequate.
One NAD was formulated for all four wealth groups.
Nutrient constraints were set so that the NAD would:
provide an energy content equal to the sum of the requirements of
all household members; provide 30% of household energy
requirements from fats; provide at least 100% of the
recommended intakes of vitamin A, vitamin C, thiamine, riboflavin, niacin,
vitamin B6, folic acid, vitamin B12, pantothenic acid, calcium,
iron, and zinc
(Food and Agriculture Organisation 2004a, b)
and would not exceed the recommended safe intake levels for
vitamin A, iron, vitamin C, calcium and niacin
Agriculture Organisation 2004a; Save the Children UK 2011)
Food consumption constraints comprised intake limits set
for food groups and food items. Food group constraints were
set as the minimum and maximum allowable intake from a
particular food group per week, based on HSS 24-h dietary
recall data, published findings, and anecdotal evidence
et al. 1993; Food and Agriculture Organisation 2004a)
Constraints for food items were defined as the allowable
number of portions per person per week. They were all set between
0 and 21 portions per person per week. The average intake of
food consumed per meal by a 12–23 month child was
considered a reference portion size and the CoD adjusted to the size
for each member in relation to their energy requirements
Portion sizes for different food types were taken from the
CoD manual, when available; if not, the portion size for a
similar food type was used
(Save the Children UK 2011)
3.1 Characteristics of wealth groups
HEA interviews indicated that 25.9%, 31.7%, 33.0%, and
8.5% households in Dhanusha were from Very Poor, Poor,
Middle, and Better-off wealth groups, respectively.
Livelihoods were dominated by agriculture. Poorer
households (Very Poor and Poor) were mostly landless or owned a
small amount of land and had limited food production. They
relied on agricultural daily-waged labour, paid in cash or
grain, or other unstable sources of income. The Middle and
Better-off were farming households and had earnings from
agricultural production, regular jobs, and overseas remittances
(Web Table 2). Median annual household expenditure (a
proxy for income) showed a gradient and was almost four
times higher among Better-off than Very Poor households
(Web Table 2). The percentage of total expenditure on food
in 2005 also varied by wealth group (Very Poor 58%; Poor
45%; Middle 32%; Better-off 24%).
3.2 Cost and nutritional adequacy of Typical Food
TFB for all wealth groups were assumed to remain constant
between 2005 and 2008. They included rice, wheat, potatoes,
vegetables, pulses, dairy, and oil, but were more diverse
among Better-off households (Table 3). Following the 2008
food price crisis, the absolute costs of the TFB of Very Poor,
Poor, Middle, and Better-off households increased by 19.2%,
22.0%, 26.1%, and 23.4%, respectively (Table 4). For both
periods, the cost of the TFB for Better-off households was
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Table 4 Cost of a typical daily
household food basket in 2005
and 2008, by wealth group,
much higher than for poorer households, but the proportion of
their income spent on the TFB was much lower. Between
2005 and 2008 the proportion of income spent on food fell
for all wealth groups, but the decrease in the proportion of
income spent on a TFB was greatest among poorer
households (Very Poor, −6.5%; Poor, −3.1%, Middle, −0.3%;
Better-off, −1.1%). However, the TFBs of all wealth groups
were low in several nutrients, including vitamin A, fats,
vitamin B12, calcium, iron, and zinc (Fig. 1). The food basket for
the Very Poor was also deficient in riboflavin and vitamin B6.
3.3 Cost and affordability of a Nutritionally Adequate
The CoD linear programming tool generated a minimum cost
NAD for the model household, and the cost was calculated for
2005 and 2008 (Table 5). In both years, the NAD met or
exceeded the nutritional requirements (Web Table 4) of
household members. However, in 2005 neither Very Poor nor Poor
households were able to afford a NAD (Fig. 2). In 2008, the
cost of the NAD increased by 28% over the 2005 cost, but the
incomes of Very Poor, Poor, Middle and Better-off households
also increased by 32%, 27%, 25% and 28%, respectively.
Fig. 1 Nutrient content of a
typical daily household food
basket, by wealth groups,
After the election of the Nepal constituent assembly in 2008,
a political decision was taken to increase government salaries
with a bias towards the most poorly paid and to establish a
minimum wage for agricultural and factory workers
of Labour and Transport 2008 Nov 18)
(Fig. 2). Despite this
increase in income, Very Poor and Poor households were still
unable to afford a NAD in 2008 (Fig. 2). To afford a NAD,
poorer households would need to spend more than their total
income on food, whereas Better-off households would need to
spend roughly one-third
(% income required to purchase a
NAD in 2005 and, 2008 for Very poor: 148%, 147%; Poor:
110%, 111%; Middle: 65%, 65%; Better-off: 38%, 38%,
We estimated the nutrient content and cost of a TFB, for
different wealth groups in a rural district in the plains of Nepal.
We estimated the minimum cost of a NAD designed using
linear programming and assessed whether the NAD was
affordable by different wealth groups, before and after the 2008
global food price crisis.
Typical household with 6 members: Boy (2–3 years), Boy (5–6 years), Adolescent girl (13–14 years),
Adult male (37 years), Adult female (28 years), Adult female (45–50 years)
a Green leafy vegetables
Although we hypothesised that the food price crisis would
have a higher negative nutritional impact on poorer wealth
groups, we found that the TFB for all wealth groups did not
meet 100% of nutrient requirements. Furthermore, the poorer
households could not afford a cost-minimised NAD in both
2005 and 2008. Although the cost of both the TFB and the
NAD increased significantly in 2008, the affordability
scenario did not deteriorate as an increase in income also occurred.
Salaries of government staff in Nepal increased after the
Maoist government took over in August 2008, which may
have also pushed up payments in other sectors, and a
minimum wage rate was established
(Ministry of Finance 2009;
. It is important to note that, despite our finding
that the price rises were buffered by an immediate increase in
incomes, our results indicate that about 57% of households in
Dhanusha would have required additional assistance to
achieve nutritional adequacy during both periods
. In addition, when the world food price was falling
between 2008 and 2009, there was 19% inflation in food
prices in Nepal
(Nepal Investment Bank 2009; Food and
Agriculture Organisation 2012)
. Some adverse effects of the
price changes may therefore have manifested relatively late in
Nepal. The study of
Geniez et al. (2014)
hypothesis. Using the same tool, they found that 58% of households
in the Mountain region and 21% in Kathmandu could not
afford a NAD in 2010–2011.
Contrary to our findings, negative impacts of the 2008 food
price crisis were seen in a number of countries, especially in
low-income countries and low-income groups within them
(Ivanic and Martin 2008; Brinkman et al. 2010; Cudjoe et al.
2010; Monsivais et al. 2010; Webb 2010; Mahajan et al.
. Several studies have assessed the impact of the 2008
food price crisis using different tools. We used the CoD linear
programming tool to formulate a minimum cost, nutritionally
adequate household diet and then assessed its affordability.
Linear programming has been used more often to model diets
at the individual instead of the household level, especially for
(Briend et al. 2001; Darmon et al. 2002, 2006)
Studies have used the CoD software to estimate the cost and
affordability of a household diet
(Save the Children UK
2009a, 2009b; Frega et al. 2012; Baldi et al. 2013; Save the
Children UK 2013b; Geniez et al. 2014)
and to advocate
promotion of food-based interventions or cash-based social
safety net programmes. Consistent with our findings, a
leastcost nutritionally adequate diet was unaffordable among
poorer households in the pre-crisis period (2005–6) in
Ethiopia, Myanmar, and Tanzania
(Save the Children UK
. The cost was higher than the average earnings of all
wealth groups in Ethiopia, whereas it was higher than the
earnings of all ‘very poor’ and some ‘poor’ households in
Tanzania and Myanmar
(Save the Children 2009a)
Bangladesh, the cost of a least-cost nutritionally adequate diet
for 2005/6 and 2007/8 was estimated using the CoD software.
The cost increased by 56% and was unaffordable for poorer
households in both periods
(Save the Children UK 2009b)
Estimation of affordability by socio-economic groups in
Nepal and other countries highlights the importance of using
context-specific data to assess the localized impact of changes
in food prices to appropriately guide policy decisions.
Our study found that a typical diet for any wealth group in
Dhanusha is still likely to contain less than the recommended
intake for several micronutrients, including vitamin A, B12,
calcium, iron and zinc; and that the cost of NADs were well
above the income levels of poorer households. Although the
TFB of Better-off households was more diverse and
expensive, it is still low in several micronutrients. Similarly, a study
examining the impact of the 2008 food price crisis in
Guatemala found disparity in intake among income quintiles,
and that households in lower income quintiles were most
likely to have diets deficient in vitamin A, B12, folate, and zinc
when food prices rise
(Iannotti et al. 2012)
. Assessment of
household level dietary diversity using HSS data in
Dhanusha (measured by consumption from number of food
groups including cereals in the last 24 h) found low diversity
among all groups (3.6, 4.0. 4.3 and 4.7 for Very Poor, Poor,
Middle and Better-off, respectively)
deficiencies were also evident from dietary surveys in rural
(Christian et al. 1998; Parajuli et al. 2012; Ng’eno et al.
. A typical food basket generally includes large amounts
of rice, providing the bulk of the energy, accompanied by a
thin pulse soup, potatoes, and vegetables, with milk as the sole
animal origin food
(Hirai et al. 1993; Sudo et al. 2006; Parajuli
et al. 2012)
. Ng’eno et al. (2017) examined dietary pattern
among socio-economic groups in the plain of Nepal and found
that the median daily intake frequencies of most food items
were 0 times, but rice, potatoes and vegetable oil were eaten
more frequently. Given the low dietary diversity, we only
included more than one item per day for cereal and vegetables in
the TFB. The number of items per food groups in the TFB was
Sudo et al. (2006)
, which was considered
reasonable, based on anecdotal evidence and consultations with field
level researchers. We acknowledge that a future study is
needed for precise estimation of dietary intake by socio-economic
groups, but do not expect that to change our conclusions
This lack of diversity in usual diets correlates with the high
prevalence of anaemia in the plains of Nepal: 50% in children
under five and 42% in women of reproductive age (Ministry
of Health and Population (MoHP) 2012). The fact that TFB
were nutritionally inadequate and that the CoD could generate
a NAD from the same local foods that were affordable by the
upper two wealth groups suggests that there could be a gap in
nutritional knowledge or behaviour, and that for this segment
of the population, communication activities that promote
increased consumption of micronutrient-rich foods might be
beneficial. Beihl et al. (2016) suggested that improving
behaviour can increase dietary diversity and nutrient adequacy in the
Nepalese population. Based on our data, we suggest that a
combination of approaches, such as food supplementation
and dietary fortification, introduction of cash-based social
safety nets, and behaviour change approaches are required.
The Government of Nepal developed a multi-sector nutrition
plan in 2012 which also suggested promotion of a combined
approach, using direct and indirect nutrition specific initiatives
(e.g. micronutrient supplementation, fortification) along with
nutrition sensitive initiatives such as cash and in-kind
transfers, school feeding, and nutrition education for various target
(National Planning Commission 2012)
The main strengths of our study are that detailed, local food
price data were collected for 64 commonly consumed items in
both 2005 and 2008, which allowed estimation of local level
food price inflation
and examination of how the
affordability of a NAD may have been affected by
membership of specific wealth groups in the post-crisis period. We
collected food prices from the same market locations in the
same season (October–November) in both years. We also
assessed the nutritional quality of typical food baskets of
wealth groups and calculated the cost of a cost-minimised,
nutritionally adequate diet, pre- and post-crisis, allowing for
a comparison of affordability.
The study had some limitations. Data were not available on
changes in food consumption or expenditure on specific food
items and it was not possible to examine substitution effects.
Food price data were collected during a festive season when
prices tend to peak and we were not able to investigate
seasonal variation. However, data were collected for commonly
consumed food items and we do not expect seasonal price
variation to be large enough to change the results dramatically.
Another limitation is that our study estimation used prices
from the most accessible rural markets, which may have been
slightly higher than farm-gate prices. Also, the prices used
were per 100 g of purchased food rather than 100 g of edible
serving. However, the poorer households needed to spend
more than 100% of their income to afford a NAD, whereas
consumption of households’ own produce is likely to only
play an important role for Middle and Better-off households.
It is therefore unrealistic to assume that the factors would
significantly change the main results or conclusions. Due to
variation in reported income, we used expenditure data as a
proxy for income, an approach which has commonly been
done in other studies using this tool
(Frega et al. 2012; Baldi
et al. 2013)
. The 2008 income level estimates were not
generated from household level data, which may have added some
inaccuracy. Nevertheless, the estimation used wealth
groupspecific income sources and changes in incomes between
2005 and 2008. We think that the changes in income data
are realistic as key informants engaged in the specific income
sources (e.g. government employees, daily labourers, specific
self-employment or other professionals) provided the data.
Future studies are required to estimate the cost of an adequate
diet during different seasons and to check the acceptability
and other factors that may affect adoption of a
minimumcost diet generated using the CoD tool.
In conclusion, our study found that the typical food baskets of
all wealth groups were deficient in micronutrients and the
nutritional impact of the food price crisis probably did not
vary by wealth group due to an accompanying increase in
income. However, the income levels of poorer households,
even before the food price crisis, were too low to afford the
minimum cost of a nutritionally adequate diet. The inability of
poorer households to afford an adequate diet and the
inadequacy of nutrients in typical diets indicate that urgent efforts
are needed to put in place targeted social safety net programs
for poor households, and to provide nutrition education for
those households who have the potential to afford nutritional
adequacy by making changes to their typical food baskets.
Acknowledgements A.S., N.A., and N.S. designed the cost and
affordability of a nutritionally adequate diet research. The study was embedded in a
larger study of nutrition, household economy, and food prices in Dhanusha,
designed by N.S., D.M., B.S. and A.C., which B.S. and N.S conducted and
managed. N.A. analysed the data and wrote the first draft of the paper. A.S.,
A.C., N.S., and D.O. contributed to the revisions, and N.A. had primary
responsibility for the final content. All authors read and approved the final
manuscript. We thank the participants, the data collectors from MIRA,
Sweta Chaudhary who initially processed the HEA data, and Dhanusha
District Public Health Office. We acknowledge the support of Esther
Busquet and Rachel Evans from Save the Children UK in using the Cost
of Diet tool; and thank Suzanne Boyd from the Wolfson Research Institute
for Health and Wellbeing, Durham University for help with referencing.
Funding This study was funded by a Wellcome Trust Strategic Award
(085417MA/Z/08/Z), and UBS Optimus Foundation. The authors are
responsible for the content of this publication, which does not necessarily
reflect the views of the funders.
Compliance with ethical standards
Conflict of Interest The authors declare that they have no conflict of
Open Access This article is distributed under the terms of the Creative
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N a s i m a A k h t e r i s a P o s t
Doctoral Research Associate in
Quantitative methods at Durham
University She has over 15 years’
experience in evaluation,
monitoring and data analysis. She
works across many projects in
applied health research including
evaluation of interventions and
advanced data analysis, teaches
statistical concept and analytical
methods, facilitates grant
applications and provides statistical
support to researchers as part of the
interdisciplinary statistic group at
Wolfson Research Institute of Health and Wellbeing. Nasima obtained her
PhD from University College London in 2013, which compared food
security and poverty assessment methods, estimated food prices inflation
following the 2008 global food price crisis and affordability of a
nutritionally adequate diet by socio-economic groups in rural Nepal. Nasima
worked as a key researcher for the Helen Keller International
Bangladesh’s Nutritional Surveillance Project, Homestead Food
Production Program and external evaluation projects (1997 and 2007).
She is experienced in design, planning, and implementation of projects
and provided consultancy for the WHO, UNHCR, Save the Children.
N a o m i S a v i l l e i s a S e n i o r
Research Associate at University
College London Institute for
Global Health. She has 26 years
research experience and has
worked in low-income settings,
mostly Nepal, for 23 years. Since
2005 she has worked on maternal
and newborn health and nutrition
trials in partnership with Mother
and Infant Research Activities
(MIRA) in Nepal. Naomi
completed her degree in Natural
S c i e n c e s a n d h e r P h D i n
E c o l o g y f r o m C a m b r i d g e
University in the UK. She has worked in participatory health promotion,
community mobilisation, and livelihood diversification through natural
resource products and beekeeping in Nepal, India, Somaliland, Sierra
Leone and Trinidad and Tobago. Her most recent research investigates
how women’s groups, practising participatory learning and action, can
improve neonatal survival and maternal and infant nutrition, particularly
Bhim Prasad Shrestha , Senior
Programme Manager at Mother
and Infant Research activities
(MIRA), Dhanusha, Nepal is
responsible for overall management
a n d t e c h n i c a l s u p p o r t t o
programmes including financial,
human resource, administrative
support along with coordination
with local, national and
international stakeholders. He has also
supported MIRA Makawanpur
programmes as a Programme
Manager and has been working
with MIRA since 2000 in various
role to support the team capacity in supervisory capacity, and contributed
to effective and smooth implementation of MIRA activities. MIRA is a
non-governmental organisation (NGO) partnered with the Institute of
Child Health (ICH), UCL and has received funding from WHO,
UNFPA, UNICEF, to test the effectiveness of interventions to improve
maternal and newborn health in rural communities. Before joining MIRA
(1990–199), Mr. Shrestha worked with national and international NGOs
in Nepal and government agencies to develop capacity of staff and to
strengthen project and programmes that aim to improve health in rural
communities of Nepal. He is a member of the Nepal Public Health
Society and Nepal Red Cross Society. He has a BSc in Public Health
and an MSc in Maternal and Child Health from ICH, UCL; and has
coauthored a number of health related publications.
D h a r m a S . M a n a n d h a r i s
President and Executive Director
of Mother and Infant Research
Activities (MIRA) – an NGO in
Nepal involved in improving
maternal and infant health through
research, training, advocacy and
service. MIRA has been involved
in many research activities related
to maternal and infant health
particularly in large cluster
randomized trials in collaboration with
the UCL Institute of Global
Health over the last two decades.
He has been taking part in many
nutritional studies, including randomised trials on multiple micronutrient
supplementation in the antenatal period, large cluster randomised trials on
participatory women’s groups versus participatory women’s groups with
food or cash supplementation to pregnant women with the aim of
improving birth weight. He has been a co-author of many publications related to
maternal and infant nutrition. He has also been Professor and Head of the
Department of Paediatrics of Kathmandu Medical College for over a
decade and a half and is a member of the Technical Advisory Group of
WHO SEARO on Maternal, Newborn, Child and Adolescent Health. He
is also a Fellow of the Royal College of Physicians, London and Hon.
Fellow of the Royal College of Pediatrics and Child Health besides other
David Osrin is UCL Professor of
Global Health, Wellcome Trust
S e n i o r R e s e a r c h F e l l o w i n
Clinical Science, and Honorary
Consultant, Great Ormond Street
Hospital. A paediatrician and
public health researcher, he is
interested in interventions to
improve the survival and health of
women and children in low- and
middle-income countries, with an
emphasis on urban health. He was
based in Nepal from 1998 to
2004, and has lived in India since
then. His areas of interest include
maternal and child health and nutrition, community-based strategies to
improve home care and care-seeking, interventions to improve the quality
of health and social services, measuring health and nutrition indicators in
underserved populations, and prevention of gender-based violence.
Dr. Anthony Costello , a re
nowned international expert on
maternal, newborn and child
h e a l t h h a s h e a d e d t h e
D e p a r t m e n t o f M a t e r n a l ,
Newborn, Child and Adolescent
H ea l th a t t h e Wo rl d H ea l th
Organization since September
2 0 1 5 . H e i s a n H o n o r a r y
Professor and former Director of
the UCL Institute for Global
Health of International Child
Health at the UCL Institute of
Child Health; a founding board
member of Women and Children
First, a UK based NGO which implements maternal and child health
programmes in poor populations. He has chaired two Lancet
Commissions on Health and Climate Change. His areas of scientific
expertise include the evaluation of community interventions to reduce
maternal and newborn mortality, neonatal paediatrics, women’s groups, the
cost-effectiveness of interventions, nutritional supplementation and
international aid for maternal and child health. He has contributed to papers on
health economics, health systems, child development, nutrition and
infectious disease, and managing the health effects of climate change. He
directed programme and project grants funded by the UK Department
for International Development, the Wellcome Trust, Saving Newborn
Lives Initiative, UBS Foundation, WHO, UNICEF, UNFPA, the Big
Lottery Fund and the Health Foundation. He has also provided
consultancy for Save the Children Fund, the World Bank, WHO, DFID,
USAID, UNDP and Saving Newborn Lives. Dr. Costello has been
awarded several fellowships: at the Royal College of Physicians,
London; Royal College of Paediatrics and Child Health; and the
Academy of Medical Sciences. He also received the highest honour of
the Royal College of Paediatrics and Child Health for his research - the
James Spence medal. Dr. Costello has served as UCL Pro-Provost for
Africa and the Middle East, and Honorary Consultant Paediatrician at the
UCL Hospital for Tropical Diseases and the Great Ormond Street
Hospital for Children.
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