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Food Policy 61( 2016) 185- 197
Contents lists available at ScienceDirect
s ".,'°' ' __
FOOD POLICY
Food ELSEVIER
Child
journal
quality in
dietary
homepage:
Policy
www. elsevier.
Nepal:
rural
mom
com/ locate/ foodpol
Effectiveness
community- level
of a
®
CrossMark
development intervention F. Darrouzet- Nardi ' ,
Amelia
C. Miller , Neena Joshi ,
Laurie
Mahendra Lohani d,
Shubh Mahato ,
Beatrice L. Rogers b Allegheny College, Meadville, PA, USA
b Tufts University, Boston, MA, USA Heifer International Nepal in Katmandu, Nepal
dHeifer International in Little Rock, AR, USA
ARTICLE
Article
INFO
ABSTRACT
history:
Received
18 June
Received
in
form 22
revised
Accepted 31
Nutrition- sensitive agricultural interventions have the potential to improve child dietary quality in rural households, as evidenced by a growing body of work which concurrently measures agricultural and nutrition indicators. Our objective was to investigate whether children in rural farming communities of Nepal participating in a community- level, nutrition- sensitive development intervention had improved dietary quality compared with children living in non- participating matched rural communities. Six rural communities of Nepal where livelihoods were predominantly agricultural were selected to participate in the phased implementation of a community- level development intervention by Heifer International. Households and children in each community were surveyed at baseline, and follow- up surveys were implemented every six months for twenty- four months. Detailed data on food consumption for children older than 6 months of age were collected using a 24 h recall for 17 foods and food groups; parents
2015
2016
March
2016
March
Keywords:
Child
dietary diversity
Smallholder farms Impact
evaluation
Nepal Animal
responded
foods
source
Community based interventions
for children.
of covariance
model
A difference-
in- differences
were used to analyze
model
the resulting
with
household
fixed- effects
panel data. Results
indicated
and
an analysis
that the impacts
of the intervention varied by agro- ecological region and by season. In the Hills region, which is poorer on average and more conducive to livestock production, children who had received the intervention for two years were 2. 2 times as likely to have consumed as likely to have achieved source
foods
minimum
as children
dietary diversity
who received
food from an additional
food group, 1. 27 times
and 1. 38 times as likely to have consumed
the intervention
animal
for only one year. In the Terai region, which is
more conducive to crop production, there was no significant change in dietary quality attributable to the intervention. of communityactivities opment
These results provide level
development
were disparate activities
evidence
activities.
across communities
for particular
locations
that particularly
Given
vulnerable
that the effects
families
within the same country, we conclude
is necessary
and
ment,
nutrition
labor productivity,
Thomas,
2007;
Black
is
and
et
essential
and
al.,
development devel-
Ltd. All rights
reserved.
quality- often measured by dietary diversity- is a direct determi-
motivation
nant of nutritional Adequate
level
that tailoring
for success. 2016 Elsevier
Introduction
can take advantage
of community-
for
child
growth,
health throughout
2013;
Alderman
et
develop-
life ( Strauss
al.,
2006).
and
Dietary
status, especially for key micronutrients
vitamin A and iron, ( Arimond
et al., 2010; Arimond
such as
and Ruel,
2004), which are found predominantly in animal sourced foods. Although somewhat lost in myriad other goals, ending hunger
and improving agricultural productivity are targets of the newly launched This is
not
paper
represents
currently
publication
at
original
work
being considered by Policy, it will not be
Food
that
has
another published
not
been
journal,
published
that
and
elsewhere
in
the
previously, if
that
accepted
for
form.
Each
same
author has seen and approved of the contents of the manuscript.
Corresponding Meadville, E-
mail
author
at:
Allegheny
College,
520
N.
Main
Street,
PA, USA. address:
adarrouzetnardi@allegheny. edu(
http:// dx. doi. org/ 10. 1016/ j.foodpo1. 2016. 03. 007 0306- 9192/© 2016
Elsevier
Ltd.
All
rights
reserved.
A. F. Darrouzet-
Nardi).
Box
E,
Sustainable
Development
Goals ( SDGs),
listed
together
under Goal 2: Zero Hunger( UN, 2015). Ensuring high- quality diets for rural children number
in low- income countries
of strategies,
including
can be addressed
by stimulating
economic
by a
growth,
implementing nutrition- specific programming, or implementing nutrition- sensitive programming ( Headey, 2013; Black et al., 2013;
Ruel and Alderman, 2013). The intervention
evaluated
here
186
is
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
a
nutrition- sensitive
program,
determinants
immediate
the
does
which of
directly
not
nutritional
address
Ruel
status (
and
and economic development. Heifer activities focus on the distribu-
tion of livestock
and training
to rural women' s groups
with an
Alderman, 2013). Being forced to pick between any one of these three major strategies is— at best— a false choice, and the effective-
emphasis on income generation. These activities
occur within the
context
of social
strategy will likely depend on specific local context. Regardless, it is important to assess whether and how different
specifically citizen empowerment, values training, social mobilization, group savings and micro- lending, and enterprise.
ness of
types
one
any
of
programs
vulnerable
areas
in April
earthquake
Aguayo
people(
2015
dietary
child
this
level,
and
paper
5. 6
million
the
over
effectiveness
development
improving long- term. To
and
recovery
status
the
dietary
child
a suitable
nutritional
assesses
nutrition- sensitive
improving
on
devastating
with
quality
this
end,
a
about
severely affecting
be important for supporting
will
diets, especially in
child
experienced
2015). Leveraging existing non- governmental diverse programming experience in Nepal
al.,
et
as
of
NGOs)
organizations(
for improving Nepal which
work
such
of
a
intervention
community-
in
a using quality study design which
community- level randomized average treatment effect on the treated( ATET).
Nepal
rural
matched-
pair
estimates
the
of a strong
focus
on the development
capital,
The nutritional effects of Heifer activities in agriculture and in
women' s empowerment
have been formally
evaluated
recently;
the promotion of livestock ownership by Heifer programs was an important mechanism leading to improvements in anthropometric measurements Nepal (
Miller
of children
in Rwanda ( Rawlins
et al., 2014)
and
2014).
However, impacts on child dietary quality have not been yet established, and nutrition is not directly et
al.,
a focus of Heifer programming. To this end, we evaluated the effect of a holistic community- level nutrition- sensitive intervention child dietary diversity and animal source food consumption rural
on in
Nepal.
Potential pathways of impact Child diets in Nepal and nutrition- sensitive
interventions There are four broad potential pathways through which agricul-
Inadequate
DHS)
Survey (
6- 24
months
dren
were
a problem
health
of public
Findings from the 2011
Demographic
in Nepal
for
in Nepal.
significance
Health
dietary quality is
child
indicated
that,
children
and aged
in the 24- h preceding the survey, only 28% of chilgiven foods from at least 4 different food groups, 46%
of children
consumed
consumed
food
a
a
rich
food
in
rich
A,
24% of
children
ICF International,
2012).
vitamin
in iron( MOHP
and
and
concerns
for
exist
predominant
the
population
older
is
82%),
rural (
age
groups
fluctuations
so
across
dietary
and
ICF
seasons may exacerbate development ( MOHP and
Bank,
2012;
Maleta
et al.,
Nutrition- sensitive may
the
ameliorate
tions
on
nutrition
improvements
noted
in
2015) found that
et
child
the
impact
World
diversity
smallholder
2013).
fluctua-
However,
of
for
evidence
animal
a
interven-
of agriculture
and
focus
agricultural of seasonal
low quality
overall
2012),
al.,
an
effects
Alderman,
and
of
an
with
food
source
recently Smale farmer adoption of hybrid though
et
al.
maize
positively associated with dietary diversity in Zambia. The impacts of community- level, nutrition- sensitive activities in farming regions on improving child diets are difficult to measure and was
inconsistently a
specific
Bezner
nutrition
Kerr
A
2009).
et
maternal
some
empowerment,
uses
to
Bhutta
agriculture
were
though
of
and
infant
training
as
300
be
production,
aspect
of the
improved
diets
were
with
chil-
young
et
on
the
or
nutrition
by
Malapit
al. (
2015),
child
indicators
feeding of
rela-
and who and
women' s
or
through
Second,
increased
increased
incomes
could dietary
consumption
incomes.
Third,
of the
child
nutrition
outcomes.
The
latter
mechanism
relates
directly to the design of the Heifer intervention, which focused on developing and facilitating women' s self- help groups. Therefore, for those women
who had been exposed
to the intervention
that they would be better
able— whether through increased knowledge, increased household resources,
improve
or
increased
power
over
household
their children' s diets, when compared
had not been exposed
to the intervention
resources —
to
with women who
for as long a period of
time. There is empirical evidence in Nepal that this is a plausible
mechanism,
as evidenced
by Malapit et al. ( 2015), who estimated
that women' s empowerment
was strongly
associated
with mater-
nal and child nutrition there.
Under this theoretical framework displayed below in Fig. 1, increasing women' s empowerment with a community- level development
intervention
could
result
in
an
outward
shift
of the
demand curve for children' s food, perhaps especially during the seasons.
For our current
empirical
purposes,
we used a
model to estimate
these
effects. Women' s empowerment was not measured for the present
study, and so it is not possible to test this mechanism
directly. We
focused on dietary quality as opposed to nutritional status for four reasons. First, the intervention address
child nutritional
was not specifically
status. The animal
designed to
husbandry
training
and goat donation aspects of the intervention may have direct relationships with animal source food consumption,
but not necessar-
ily nutritional status. Second, the short- term effects of intervention
activities may be more visible in diets than in anthropometrics. Third, there are other key factors such as sanitation which may
not.
interfere with the diet- nutrition
henceforth Heifer)
alleviation,
gender- related
due to the animal
intervention.
through
reduced- form difference- in- differences
intervention
for poverty
own
training
could
production
hungry
al.,
projects
tools
intakes
study. First, household
agricultural
2004;
is a globally active NGO in thirty- two countries. The organization the introduction of livestock and related animal husbandry International(
over
for the present
with improved
et
2015). The mediating
Malapit
and
al.,
improved
allocation
children' s
by
associated
others
et al.,
time
or
et
require
Satzinger
recently in Ghana
in Nepal
and
2008;
al.,
agriculture
and
Berti
succeed (
et
Carletto
empowerment
International
Heifer with
goal
or
2011;
indicators
nutrition
The Heifer
interventions typically
demonstrated
as
Quisumbing ( 2015) found that
focus
such
women' s status(
between
complex,
and
key link between
of women' s
tionships are
al.,
potential
dren' s diets is effects
observed,
and
able
growth
2012;
important
for longer periods of time, we expected dietary
and
dietary
child
Girard
consumption (
insults to
production,
improvement of women' s social standing could lead to more desir-
in food availability
International,
interventions
health
review of studies
systematic
majority
of own
is
2003).
in food availability ( Ruel
tions
the
and
consumption
issues. Three of these potential mechanisms stand out as especially
of
Agriculture
as well.
in Nepal,
76%)
occupation (
agriculture,
husbandry
study focuses on a wider age range of children than typically measured for the DHS( 6 months to 8 years at baseline), but similar
the
as synthesized by Carletto et al. ( 2015): food prices, income from
increase
This
dietary
tural activities can improve child diets and nutritional outcomes,
citizen
empowerment,
relationship.
Further work would
be needed to make connections between dietary quality and nutritional status in this setting. Lastly, dietary diversity was found to be associated with child nutritional
status, independent
of associ-
ations with income and socioeconomic status in a wide range of settings(
Arimond
and
Ruel, 2004).
Darrouzet- Nardi
A. F.
Household
in
participation
community-
Policy
2016) 185-
61(
197
187
Increased consumption of
intervention \>
level
Food
et al./
household
production
for children
1
V Improved
status
of women
in
Child dietary quality
households
participating
A A
V
Increased income from farm ire Child
activities.
nutritional
status
Fig. 1. Conceptual framework.
At the start of the intervention for each community, local lead-
Methods
ers were invited to serve on an advisory panel and as liaisons to the Study design
population
and participants
about
the
project
activities.
Data
collection
was
per-
formed by a local field research NGO, the Nepal Technical Assistance As previously described in Miller conducted of
according
Helsinki,
and
all
Parents
Protections,
study. was
gave
to
NHRC.
At
daily reviews of the data collection, which allowed rapid identification and correction of errors. Enumerators were trained at the
Reference
board in
review
Health
of
a
informed
respondents,
third
visit,
For
visit.
consent
by
each
was
beginning of the project with 6 days of orientation
non-
Human
and
obtained
participants
were
answer
their
children.
ment
consent.
any or all questions Coded, confidential files
were
control
respon-
attempts
guidelines
the
that
measurement
of
households (
docu-
to
maintained
monitor
Heifer International
for participation
in the inter-
were identified
as participating
in
or
not before the baseline survey was implemented. All participating
they or
to
rates exceeded 90% of households
each study site. Households
of
visit,
study
activities
In each community,
to include all households
vention, and participation
house-
each
refresher
Households were identified in cluster samples within each VDC,
parent
to
and
inter- observer reliability.
and invited to participate.
reminded
decline
or
quality
consent
prior
discontinue
ongoing
and maintain
written
literate
to the project,
field pilot testing in three villages not included in the study sites,
for Human and
party, according to the
from the study,
withdraw
decline to
NHRC
Office
Protection
of
Department
each
verbal
visit, witnessed
could
S.
U.
parent
prior
dents, informed
the
Council(
formance and activities of the Field Enumerators, and conducted
patients
the
as
literate
obtained
hold
Research
subjects
Tufts University Institutional Review Board. permission for the inclusion of their children in the
as well
For
Office
the
by
endorsed
Services,
human
1496), the human investigation
845, Renewal #
Research
involving
procedures
Group, not connected to Heifer. Field Supervisors monitored the per-
this study was al. ( 2014), laid down in the Declaration
et
guidelines
the Nepal Health
by
were approved
Nepal
to the
N=
431
included
were included
in the sample
for the baseline
survey
households).
Non- participating households were not in the baseline or follow- up surveys. Each participating
NHRC.
household was visited five times over 24 months at 6 month inter-
participating household were enrolled in the study. The study was conducted in three study sites of Nepal, and Nuwakot. Chitwan in the districts of Chitwan, Nawalparasi,
vals, with some minor adjustments due to monsoon or other diffi-
All
members
Nuwakot
to
procedure
was
approved
both located in the Terai
are
is located in the Hills. These
low- income
vided
consent
by
the
of each
Nawalparasi
and
by
The
subsistence
specific
areas
at
areas
are
farmers. Heifer field the
request
of
region
largely
of
Enumerators,
are
within
in pairs to conduct
ties
is
designee.
defined geopolitically in Nepal as " Village DevelopCommittees" ( VDCs). A waiting list of interested communi-
For
purposes
developed
ties
and
income
was
assigned
to
for
receive
design,
each
Heifer
local
size,
identified, based
were
natural
levels. A
interested
resources,
matched
into Group 2
months.
which
first ( Group
Group
reduces
communities.
the
head
based
on
specifically
of household
or her
standardized
the version
tools
used in
1)
or
second (
sumed
activities
1
and
risk
Group
2
communities
of program
effect
were
spill- over
Although
occasionally,
we expect
and other simple indicators
a 24 h recall is not a perfect sur-
that this
measurement
error was
perform relatively
well ( Prentice
et al.,
2011: Arimond et al., 2010). Other large- scale studies in South Asia
begincontin-
was an
random across households.' Recent evidence comparing biomarkers with different dietary recall instruments indicates that 24 h recalls
Group 2),
activities
2012). The dietary intake questionnaire
vey instrument, and might not accurately measure foods con-
predominant
ued through the entire 24 months, while Group 2 participated in Heifer activities beginning after 12 months; these activities continfrom 12 to 24
by ICF International,
of age in the household.
employ-
of agriculture
the three study sites, and randomly development activities in a staggered
later. Thus, Group 1 participated in Heifer after the baseline survey; these
non- adjacent,
was
individual 24 h recall for each child between 6 months and 8 years
pair of communi-
ning immediately
ued
with the female
questionnaire
ICF International,
on
of
either
The
traveled
the Government of Nepal and Measure DHS in 2006 ( MOHP and of comparable
availability of health care, type demographic features such as
and educational
selected
intervention one year
other
altitude,
as to the assignment
the Nepal Demographic and Health Survey ( DHS) conducted by
VDC.
study, three pairs of the three districts
each
opportunities,
practiced,
each
this
location,
geographic
castes,
of
in
communities
ment
for
maintained
were visited by Field
the visits during which a 116 item question-
naire was completed
prorural
communities, ment
with travel. Households
who were blinded at baseline
of the VDC as Group 1 or Group 2. The Field Enumerators
Nepal;
populated
activities
local NGOs
culties interfering
have (
used
24 h recall
data
to
estimate
dietary
diversity
data
Arimond et al., 2009). A 24 h recall is often used to estimate protein
If there was systematic
measurement
error in the 24- h recall, for example if
families with higher educational attainment were systematically better across all survey rounds at recalling their food intakes, this would be accounted for in the the family fixed- effects analysis with as a time- invariant unobservable characteristic.
188
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
or
intake
energy
or
calibrate
misreporting is typically Freedman to
attempt and
estimate
issue
this
so
Consumption ASF)
can
animal
are
due
and
of seventeen amounts
All the who
concern such
as
quality
birth
were
recall
vented
inter-
ingestion
age
Children
strengthening
study. foods
create
house-
or
breastfed (
the time
at
of
knowledge -
associated
to
another
bonds
means
over time, as well a means
to
spread
the
donated
to
livestock
issues.
Further details
on the intervention
in Nepal can
be found in Miller et al.( 2014).
Household
visit
age
8
to
characteristics
years
MOHP
collected
on each
household,
lines( MOHP and ICF International, 2012). The number of animals
ICF
and
was
based on household possessions and quality of housing( e. g. toilet and water facilities), and were calculated using DHS- Nepal guide-
as
by inspection
information
including socio- economic status ( SES), animal ownership, annual income, and amount of land owned. Scores for SES were largely
in detail
excluded
owned was converted
of
to a standardized
score using FAO Global
criteria
Livestock Units( FAO, 2013). At baseline, households owned a vari-
which they were handicaps that pre-
ety of animals, including cattle, oxen, buffalo, sheep, goats, pigs, and poultry. At baseline, 14 households had no livestock. This
at
or children
survey
in
were
with
number
severe
diminished
12 month
excluded.
point,
to
and
2 0
households households
with with
no livestock no
livestock
at the at
the
24 month point. Poultry was the type of livestock most commonly owned, followed by goats. Livestock holdings were not measured
of the intervention
Details
community
sustainable
economic
each
enrolled
in" to the entry
neurologic
diet for
of a normal
were
determined
first
the
as
Allen,
foods from
assessed
of age
who " aged at
a
well
throughout the community. " Cornerstones" training ensures selfhelp practice in community members on a broad range of socio-
of
especially
and
as
Passing on the Gift" thus forms a basis for further
but did not ask about
were
months
was
physical
illnesses
current
if
goats -
Demographic
completely
Child
with
donated
group member."
methods.
in the study
Children
recipients to agree to provide the first female offspring of the
occasional
Murphy
asked
were consumed,
be
to
certificate.
enrolled
eligible.
that the
meaningful,
at baseline (
Children< 6
2012).
the Gift" to their neighbors. Acceptance of this gift requires the
consumption
participating household were health of children age 6 months
likely
International,
sourced
of each
the study.
were
they
present
can signal
study. Diets and resided in participating households of
for the animal
healthy foods is important,
2014). The 24 h
or preparation
mass
This
While frequent
them.
other
food groups
members
part
the
protein
setting is nutritionally
et al.,
body-
study did not intake from the 24 h recall,
in the diet
rare
and
index
questionnaire,
with
2003).
al.,
et
foods
afford
in this
Rawlins
correlated
of major
to the low dietary
2003;
as
not
typically
foods
source
or
additional
occasionally
consumption
Kipnis
energy
was
of
which
hold
2014;
al.,
et
food frequency
a
positively
at the 6- and 18- month observation points.
As previously consisted
of
described
in Miller et al.( 2014), the intervention program of 12- month long participatory
a
Dietary quality indicators
community- level development activities led by Heifer field staff, specifically
tailored
for
International
Nepal,
2014).
the
in
situation
The Heifer
citizen empowerment, and poverty alleviation, development, with a strong emphasis on optimization
based in
Self-Help Groups
women' s
household
members,
facilitator. These
course
of
designed
and
are
workshops,
promote
sometimes
biweekly
meet
the
cohesion
activities
involve a
Heifer and
dietary
(
including animal
reforestation
use
of
addressing livestock into the
of
the
environment),
der
awareness (
household), Nepal,
and
promoted
questionnaire were aggregated into the commonly used WHO diet-
The
ary diversity indicator(
participation
saving biogas), improving health and husbandry, and
improvement
was established
pest
not
Kitchen
gardens
the Heifer
child
diets,
training
nutrition,
or
curriculum
does
health. Baseline
not
staff suggest
that
members
community
are
dominant
were
of
dietary
and also because most children
patterns
groups, the MDD indicator
at baseline is applicable
in the
and
across
various
quality arose with the addition(
age
in this case, even for chil-
dren older than 24 months of age. The widest variation
specifi-
aware
equal to one if the child
study consumed foods from at least three groups: typically a starchy staple, pulses( dal), and then oil( WHO, 2010). Given these pre-
knowledge
generally
milk and dairy
of interest, MDD,
sen as a cut- off for the number of food groups, in accordance with
in dietary
or not) of the fourth food group,
that is, if a fourth food group was consumed at all by the child. The third outcome of interest, ASF, was constructed as a binary
of the nutritional benefits of animal source among participants foods was not measured. Anecdotal qualitative reports from Heifer
field
as a binary variable,
WHO recommendations,
way to generally improve household diet; however, a specific focus on nutrition improvement for the
Notably,
address
techniques.
nuts, and seeds;
second outcome
in the previous 24 h period) at time t and zero if not. Four was cho-
of
household income, encouraging gendecision- making on benefits for the
management
legumes,
achieved MDD( defined as having consumed any four food groups
increasing focusing
eggs;
products ( WHO, 2010). The
practices
animal
ecosystem
WHO, 2010). Thus, seven food groups were
starchy staples ( grains and white potatoes); vitamin- A rich fruits and vegetables; other fruits and vegetables; organ meat,
planning for the future ( Heifer International Participating households also learned about com-
as a
was
program.
tree-
and
agricultural
had
is
program
and
2014).
posting
cally
and
sustainable
management (
integration
there
using
to indicate
Neumann et al., 2003; Ruel, 2003; Steyn et al., 2005). To calculate
meat, and fish;
community accountability
resources,
calculated
DDS and then MDD, the seventeen foods and food groups in the
devised to
encourage
was
the
created:
sharing
MDD)
consumed any animal sourced foods ( ASF) was constructed
for holistic community training is based on the" 12 Cornerstones" modules development. Each " Cornerstone" has specific training
via
into seven groups( WHO, 2010). Then,
diversity" (
food groups. Finally, a binary indicator of whether children
other
self- reliance.
foods, aggregated
minimum
whether or not the child had consumed foods from at least four
are
interac-
specific
seventeen "
trained
training. Over
and
months,
community
community of livestock
with
by
supplemented guidance,
12
approximately
to
These
generation. which
which
meetings
instruction,
tive
income
to
as a means
Dietary quality was represented as three outcome variables of interest. First, a dietary diversity score( DDS) was calculated from
focuses
curriculum
on
management
Heifer
Nepal (
rural
training
variable indicating whether the child had consumed any ASF (
meat, fish, eggs, or dairy) in the previous 24 h.
the nutritional benefits of animal milk, frequently offering it to the elderly, sick, and children when it was available. At the conclusion of the first year of involvement activities,
two
households,
meat-
with
the
type
goats
proviso
were
that
these
donated first
to
Statistical
participating
recipients "
methods
in these
Pass
on
To assess program effects over the two- year study period, we estimated
a
difference- in- differences
model
which
incorporated
household fixed- effects'
key
Nepal.
as
results
between
by
region,
Hills
the
due to the in
Terai
the
and
et al./
model to estimating the difference- in- differences impact of the intervention, we first performed paired sam-
t- tests to
how dietary quality
assess
sex, and
geographic
exploratory
regression
age,
an
stratified
Darrouzet- Nardi
Food
Policy
region
of
varied
with
child.
to
estimate
analysis
key factors
Then,
the
the
such
conducted
we
associations
2016) 185-
61(
197
189
the difference- in- differences test of program
model, which served as the formal
effects.
Difference- in- differences estimation was selected for this study
Before the
assess ple
and
differences
agroecological
A. F.
because we had panel data to take advantage of, and difference-
in- differences
can address endogeneity
sent whenever an intervention
issues, which may be pre-
is not randomized
at the individual
level.
between the treatment variable and dietary quality indicators. Using obtained from this exploratory analysis, we information designed the difference- in- differences model to estimate the average
the
treatment
effect
compared
the
An
the
is
a
in- differences
useful
is directly
rounds
an
more
quality. difference-
with
rounds
outcomes
of
differences
data
of
McKenzie,
endline(
we
analysis
dietary
child
compare
when
between
autocorrelation
with
significant
on
tool to
analytical
especially besides just baseline and
low
tively
results
treatment
of
estimates,
ANCOVA, the survey
levels
various
ANCOVA
collected
intervention. Finally,
the
of
ANCOVA), to test for statistically
covariance(
between
the treated( ATET)
on
difference- in- differences
2012).
are
In
interest
of
an
across
incorporated. Child
diets may have relaespecially across different seasons, and food groups such as animal sourced foods.
autocorrelation,
especially for
particular
variability and low autocorrelation of these dietary outcomes be exploited with ANCOVA to improve statistical power over a
The can
difference- in- differences the
remove
to the
2012).
An ANCOVA
can
that
due
treatment
average
outcomes
effects
was
across
survey rounds. the dependent variables
In the exploratory regression, were the DDS, MDD and ASF indicators of dietary quality. The independent variables were child age, child age squared, child sex, household size,
women' s
Villages were randomly assigned to either Group 1 or Group 2, but within villages, households
pation
in the
level,
education
income, and geographic
season
of
measurement,
region. Notably, although
annual
intervention,
intervention
significant
predictor
regression.
Income
was
24-
and
at
months,
the
hungry hungry
the
the 6-
the
study
be
to
likely
subsistence-
be
should
on
starting after the baseline survey was implemented.
Statistical
the
29%
receiving foreign
for
for Nepal
income
identification
incorporating
fixed-
effects
scores
the
and
estimates
included
season
was
or
Bank,
best
the
the
design and the near universal participation within
each community,
and thus reduced concerns for selection bias. This
strategy is especially useful given that we are concerned with the broader effects of the community- level intervention on individual effects
diets. Concern
with
of the intensity
the
but still important-
separate-
of household- level participation
in the
program may have merited a different analytical strategy, such as propensity score matching, as utilized in Rawlins et al. ( 2014) who explored the Heifer program effects in Rwanda.
Dietary Quality
it=
of+/
f
lit+ B2Pt+
Q6 Cit+
P3( lit* Pt)+
fl4St+
135( lit* St) 1)
µt
Eq. ( 1) above was the difference- in- differences
model used for
was
an indicator
of how long ( in years)
received the intervention at time t( Intervention=
a child
had
0, 1, or 2 years).
It was included in the model to capture any differences between Group
1
Group
and
2
at
baseline. The P("
Phase")
variable
was
a
binary indicator of Phase 1 ( P= 0) and Phase 2( P= 1) of the intervention. The Phase variable was included
to capture the time-
variant factors which may affect the dietary quality outcomes of interest, irrespective sible exogenous
of being in Group 1 or Group 2, such as pos-
variation
in agricultural
productivity
year to year,
were
were pooled into two groups from the original five time points to obtain consistent standard error estimates( Bertrand et al., 2004).
or unmea-
Therefore, to
control
regression
varied
by
effects
into
binary indicator
and randomized
implementation
incomes,
option
as
the
for example from a drought or a pest infestation. The time phases
of program
as a
in
con-
households, instead
incomes
from the phased
received
many
2012)their
part of
households.
across
in
that
unobservable
among
from the exploratory
we stratified
nal groupings
reflect
differences
socioeconomic
Results
therefore,
as a substantial
rea-
variable
given
who
variable
during
diversity
came
households
surwith
two
are
in
impact evaluation of the Heifer intervention. The I(" Intervention")
is that income
reason
World
as a whole(
heterogeneity
unobservable
there
as a control
dietary
with
might
household
incorporating
used
The first
model.
remittances
invariant
time-
not
study setting. Moreover,
of remittances
receipt
ables.
The
points.
children
and
months,
coincident
annual
However,
valid.
was
codetermined
agriculture
households-
trol
month
exactly
Although measuring
season.
why household income the difference- in- differences
sured
therefore
12-
season
of
years
and
18-
month or
was
sons
is
baseline,
for selection
intervention
in the exploratory
ASF
or
at
potential
intervention
annual income
may lead to systematically lower estimates of due to the recency effect, income measurement across
income the
not
for income
schedule
vey
MDD
of
measured
the
sites ( approximately 90%). Using a difference- inmodel allowed us to estimate the ATET of the Heifer
differences
improved over the course of the 24- month study, it was not a statistically
could choose their level of partici-
creating
bias, despite the near- universal participation of households in the
children' s
dietary
antecedent
McKenzie,
model (
in the
variation
Identification strategy and selection bias
of
vari-
region; regio-
in
variable
For Group the
1, the baseline
6- month,
constituted 12- month
12- month,
the
Phase
observations
observation 18- month
2.
For
constituted
and
Group
Phase
24 month
2,
the
constituted Phase
baseline
1
1, and
observations
and
through
the
18-
and
24- month observations constituted Phase 2. Thus, Phase 1 indicates those who had been exposed
to the intervention
less at the time of measurement,
and Phase
for 6 months 2 indicates
or
those
who had been exposed to the intervention for 12 months or longer
at the time of measurement. Along with the benefit for econometric analysis of obtaining consistent standard error estimates, pool2
able
this
fixed
Household
characteristics
effects
of
incorporated in
were
households
study, household data
were
that
remained
collected
order
to
constant
from
for
control
the
across
study
with
along
respondents,
unobserv-
any
For
period.
child- specific
variables. But, some key variables cannot be measured, such as each household' s joint the motivation in providing healthy diets for their kids, or their excitement about Heifer
intervention.
International
regression,
each
categorized
in
unit
non-
Just
of observation(
overlapping
like
with
children,
groups(
such
country-
in the as
case
level fixed of
the
households, in
present
the
in
effects
a
study)
case of
the
panel can
be
present
then enter as a constant term ( over time) in the differencestudy), which in- differences estimates. One child per household need not be picked out to use for measurement
household
over
of
household
the
study
fixed
period.
effects,
because
each
child
belongs
to
only
one
ing the five time points
of observations
Phases explicitly
recognizes
the intervention
to be immediate(
The
I*
P ("
Intervention*
into these
longer
two
that we did not expect the effects of Phase")
Bertrand et al., 2004). variable
was
an interaction
term of the I and P variables. The coefficient on this term was the estimated ATET of the intervention on those children who received
the intervention starting immediately after the baseline survey. The ATET was the difference in the average outcome across Phases
1 and 2 for Group 1, minus the difference across
phases
in the average outcomes
for Group 2. The difference for Group 2
was
subtracted
190
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
from the difference impact also
1 to
with
any
have influenced dietary
could
the I*
cient on
for Group
intervention
the
of
P
ferences." Table
conflation
time-
was
Groups.
factors that
estimated
coeffi-
Group
difference in the dif-
the"
below describes the three different
1
Table 1
the true
of
variant
The
outcomes.
therefore,
variable,
avoid
other
intervention levels, by the length
groups
of
harvest
were
the
during
made
season ( S= 0). Season was
hungry
season (
included
S=
1)
2
2
2
2
6
12
18
24
0
6
12
18
1
1
1
2
2
0
0
0
1
1
0
1
1
1
1
0
0
0
1
1
0
1
1
2
2
0
0
0
1
1
ATET,
and
years)
P)
I* P
of
The
I*
P variable
was
used
to
estimate
the
also
24
served
as
the
different groupings for ANCOVA.
in order to control
for the impact of seasons on the dietary quality outcomes,
which
whole, effect sizes are smaller in magnitude, but statistically signif-
in preliminary analysis. The I* S (" Intervention* Season") variable was an interaction term of the I and S indicators. was
2
0
Note:
the
or
1
1)(
Value
observations
1
months)
has been taking place, and the phase for each group. The S(" Season") variable was a binary indicator of whether the
vention
1
Intervention( Phase(
time the
of
1
Observation(
inter-
to the
exposure
1
observed
icant and potentially
useful from a policy perspective.
This variable was included to allow for the fact that the intervenimpact may vary by season, due to nonlinearities in the impact of the intervention such as seasonal fluctuations in food availabiltion
The of term represented the household fixedhousehold is unique, and may have unobservable
ity.
which
correlate
of child
with
child
characteristics,
and
this
Estimating
erties.
allowed
us
to
is
model
term
an error
using
impact
the
assess
dietary quality. Cit u; t
as
represents
the
with
each
a vector
prop-
household- level fixed-
effects
intervention
on
child
household, by effectively quality within each specific removing the impacts of unobservable, time- invariant household because
Standard
not
Wooldridge, 12. 0(
be
to
expected
errors
the
of
observations
within
were
household
a
Bertrand
analyzed
household
by
clustered
child
independent (
Data
2002).
were
same
StataiMP
using
were
2004;
al.,
et
version
(
characteristics.
statistics
Descriptive
and summaries
statistics
of
across groups
at baseline indicate that randomization was relatively successful Table 2). Mean household characteristics, including annual household income, and socioeconomic
ownership
did not differ
status, household
between
Groups
size, and land
1 and 2 within
each
study sites, as expected since these groups were assigned randomly ( Miller et al., 2014). However, animal scores at baseline
were different between Group 1 and Group 2. Further details on the randomization can be found in Miller et al.( 2014). The analyt-
ical design allowed us to account for this difference by controlling for baseline household characteristics.
2011).
StataCorp,
1- 3 present the descriptive
key household
dietary
characteristics.
Tables
characteristics
usual
the Heifer
of
effects,
Household characteristics
There
were
significant
differences
in baseline
characteristics
between study sites in the Terai and the Hills( Table 3). At baseline, the
Exploiting We
multiple
utilized
survey
difference- in- differences McKenzie (
2012).
dependent
dietary
levels
the
of
as
a
estimates,
This
model
outcome
tests
while
for
comparison
the
following
same
controlling
for
are
the
pooled
in
specification
the
whether
the
variables
treatment,
in the Terai had higher mean annual income per house-
hold( one- sided two- sample t-test, p= 0.000), larger mean house-
ANCOVA
an
households
rounds
across
the
of
means
different
lagged
dietary
outcomes.
hold
size (
mean
two-
one- sided
women' s
p= 0. 000) than the Hills ( Table 3). At baseline,
p= 0. 000) than the Terai ( Table 3), a finding consistent ecological
literature(
3i DietaryQuality
t_
3214+ EAt
1+/
t=
to 271
1
t
Eq.(
DietaryQuality;, t 2), and
patterns rent and lagged dietary quality child
for
i
at times
t
by as described and outlined in Table 1 binary indicators mation
and
These
for
to
each prevent
the usual
across
ical
properties.
model is ( 32.
survey
perfect were
represent
collinearity;
is a
constant
which is dropped
andµ;,
coefficient
tis an
error
of interest in
analyzed using
term;
over the study period. The number
76
at
baseline
to
134
at
(
cur Child dietary is Dietary esti- child
age,
quality-
region, and
measured by
DDS,
MDD,
season of
term
version
with Tables 5- 7 below present analyt- same
12.
0
and
measurement.
ASF- varied Figs. 2
age
base-
dietary groups
quality
or
patterns.
indicators did not vary
appreciably
sex ( Tables
child
6). Children in the
and
5
line ( mean
DDS= 3. 05,
SD= 1. 19, one- sided two- sample t-
p=0. 000);however, mean DDS, MDD, and ASF did not differ
Results other age groups nor by sex(Tables 5 and
among
6). Over the study
period, the lower DDS for the 6-12 month age group section
of baseline
null
ysis
cannot
the
not
key
the
groups,
intervention'
s
the
effects,
then
and finally
tion using dif erencethese results
detailing
comple- improved key
results
of
and
demonstrate that the indicators of
exploring
the
differences in-
mean
is
most
pressing.
dietary
the
ANCOVA
When
the 12-month
patterns
across
be
rejected ( one- sided two- sample ttest,
evalua-
shown). The
results for the impact
methods.
Overall, inclusion or exclusion of the youngest age significantly dietary diversity at baseline was the
and mentary foods were just being introduced(
season, when the
results for
the
sample
persisted across
observation, where
the
p=0. 29, ttests
impact
Heifer intervention in the Hills,
estimating
points except
mediated hypothesis that the DDS across all age groups was the same
child dietary quality
baseline). this effect was greater during the hungry need
anal- time
results in detail, starting with an household characteristics that may have
presents
and 3
findings for the dietary
2011). 12 month age group had the lowest mean dietary diversity at test:
This
with > 10 24- months
for
this
StataiMP
from
It,
StataCorp, 6-
all
with the
the
above; At is a set of five
round, one of
Our main
Data
t_ 1
increased
2) Table
indicators( DDS, MDD, and ASF)
respectively;/ 30 1,
t-
and
DietaryQuality,
changed
at 24- months, and the number of households
chickens
µ;
4). In
in the
Metz, 1989).
Livestock holdings 30+/
households
Hills had a higher mean animal score( one- sided two- sample t-test,
of households with at least one goat increased from 197 at baseline
5
DietaryQualityi =/
t- test, p= 0. 015), and higher level ( one- sided two sample t-test,
sample
education
as
a
3 Except
for
the
youngest
age group, 6-12
month
evaluation
were robust to
group, for which
lowest, likely because
n= 87 at
A. F.
Darrouzet- Nardi
et al./
Food
61(
Policy
2016) 185- 197
191
Table 2
Characteristics at baseline across districts between Group 1 and Group 2. Household
Units
of
N
characteristics
measurement
income
Annual
Households
Nepali Rupees
59
SES
Animal
Household
score
Global Livestock
87, 610
1. 38
0. 79
5. 38
1602
117, 581
0. 91
0. 86
2.
08
3205
units
owned
m2
Wealth index
year
per
Number
Land
size
of members
Group 1 in Chitwan Mean SD
Group 2 in Chitwan Mean
44
SD t- test p-
value
65, 434
1. 70
1. 61
5. 41
2741
46, 225
0. 99
1. 86
1. 87
2583
0. 235
0. 096`
0. 004-
0. 962
0. 056'
71, 799
1. 48
2. 80
7. 16
3184
59, 414
1.
10
1. 62
3. 02
2443
Group 1 in Nuwakot Mean
59
SD
Group 2 in Nuwakot Mean
72
SD t- test p-
63, 930
1. 19
2. 95
5. 93
3348
64, 301
1. 16
1. 67
2. 19
2234
0. 161
0. 558
0. 007-
0. 688
0.
value
473
Group 1 in Nawalparasi Mean
62
SD
92, 258
2. 02
2. 80
6. 69
3779
94,711
1. 28
1. 62
2. 84
4481
85, 191
2. 22
2.41
7. 57
4163
1. 11
1. 84
3. 69
5495
0. 669
0. 354
0. 005"
0. 113
0. 666
78, 019
1.
66
2. 07
6. 41
3189
84, 014
1. 16
1. 77
2. 84
3789
0. 178
0.617
0. 976
0. 103
Group 2 in Nawalparasi Mean
68
SD
92,
t- test
p- value
875
All study sites Mean
364
SD t- test
p- value
0. 000"
Notes: Chitwan and Nawalparasi are districts located in the Terai region. Nuwakot is located in the Hills region. T-tests were performed to test the differences in means
between each group, within each of the three districts, and then for the sample as a whole at baseline. Two- sample t- test with equal variances;" p<. 10. p<. 01.
Table
3
p<. 05.
Child dietary patterns across age groups and sex at each obser-
Difference
in
for household
t- tests)
means (
characteristics
across
agroecological
vation point were analyzed using the 24 h recall data( Tables 5 and
regions.
Annual
Household
Women'
income
size
education
Nepali
Number
per
rupees
year
Animal
s
Global
Categorical
of
6). At baseline, almost all children consumed a starchy staple( 96%) and oil( 94%) in the previous day, while many children consumed
score
people
dal( lentils)( 43%),
livestock
and other
fruits
and vegetables(
38%),
and smal-
e
ler
units
proportions
rich
fruits
and
of children vegetables(
consumed
meat (
34%) and Vitamin- A
9%). Mean DDS at baseline ranged from
Region
Hills N=
65, 071
71, 753
5. 00
2. 21
2. 87
2. 78 food groups ( 6- 12 month age group) to 3. 81 food groups
6. 27
3. 21
1. 66
MDD (
19- 24 month
225)
Terai
N= 364) Difference Pr( T<
t)
-
6682
1. 27
0. 048"
or
-
1.
0. 200
00
age 5)
group).
ranged
Across
age groups,
from 22% of children (
achievement 6- 12 month
of age
group) to 58. 6% of children ( 37- 60 month age group). Consump-
1. 21
o. 000"'
Table
tion of ASF ranged from 44% of children ( 6- 12 month age group)
o. 000"'
65% of children ( 37- 60 month age g group) ( Table 6). Dietary quality indicators differed between the Terai and the Hills( Table 5). to
Two-
t- test
sample
with
equal
some or
school;
primary
beyond."
p<.
05.
p<.
01.
p<.
4:
The
variances;
categorical, where 1: no education; finished
women'
s
education
is
variable
2: literacy classes, non- formal education; 3:
primary
school;
5:
some
secondary
school;
6:
SLC
In general, DDS was higher in the Terai than in the Hills( one- sided
two sample t-test: p= 0.05). Mean MDD was also higher in the Terai( one- sided two- sample t- test: p= 0. 00), but ASF consumption
10.
was higher
x.,
in the Hills ( one- sided
two- sample
t- test: p= 0. 00)
Table 5).
Dietary quality indicators varied across seasons( Fig. 1). Seasonal distribution of DDS differed, as more children achieved higher dietTable
ary diversity
4
Change in livestock Number
of
ownership
households
across
with
goats
all
study
sites
between baseline
Baseline
12
377
421
months
24- months.
and
24
months
the
hungry
during
scores
54. 5%)(
seasons(
households
None 1 2
2 Number 0- 5
of
households
with
harvest
seasons(
73. 7%) than during
Fig. 2). DDS were systematically higher
during the harvest seasons compared to the hungry seasons( mean plus SD= 4. 13 plus
Total
the
1. 07 vs. 3. 67 plus 1. 11,
two- sample t-test,
415
p< 0. 001) (
Table
4).
This
pattern
was
seen
in
both
regions
166
36
49
34
14
16
p= 0.006 in the Terai, p= 0.000 in the Hills). There was an apparent disappearance of the ' hungry season' for the Terai Group 2 at the 12- month observation point, indicating that something was con-
37
37
38
136
238
217
206
tributing to better dietary quality in that region( Fig. 2). Thus, there
poultry 133
103
6- 10
89
86
73
10
76
113
134
were seasonal patterns in dietary quality across both regions( Terai and Hills). Overall, the children March
and
April than in October
achieved and
better dietary quality in
November( Fig. 1).
192
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
100. 0
4
90. 0
O
80. 0
8
r
70. 0
D
60. 0
d50.0
40. 04
C4 C4
30. 0 o
oip
20. 0
0
10. 0
y
0. 0
u•
6- Months
Baseline Terai
1 ——
Group
12- Months
Terai
Group
2 —
18- Months
Hills
1 ——
Group
24- Months
Hills Group 2
Fig. 2. Percentage of children achieving minimum dietary diversity, over the study period. Note: N= 377 households at baseline, N= 377 at 6- months, N= 421 at 12- months, N= 423 at 18- months, N= 415 at 24- months.
45
4
40-
E 35u
30-
0 on
C" 0 2015u
10
d 5 a
J
0 DDS= 1
DDS= 2
DDS= 3
DDS= 4
DDS= 6
DDS= 5
DDS= 7
DDS= 8
Fig. 3. Dietary diversity scores( DDS) by season. Note: DDS is the dietary diversity score. Black bars indicate the distribution of dietary diversity scores in the' harvest season', and gray bars indicate the distribution of dietary diversity scores during the' hungry season.'.
Impact
The
evaluation
reduced Exploratory ables
are
levels,
and
that
was
Intervention*
the
differences This
coefficient estimated
ratios,
that
so
indicate
no
variable.
Results
the
24 h
show
that
have
to
1.
27
times
1.
38
times
children
as as
likely likely
in the Hills
year.
to to
who
coefficient
of
the
children
0. 981
coefficient
achieving ASF
equal
to
control
or
in the Hills
who
is
of a child
consumption
one
after odds
would
explanatory
had
received
consumed
received
the
ASF ( p= 0. 001) as intervention for only
model
season,
and
the
in
shows
both
that
the
Hills ( Odds
MDD
Terai (
was
Odds
Ratio= 0. 069,
for DDS and MDD, respectively), but it did not mediate the impact intervention
were
have
p= 0. 007)
Ratios=
the
hungry
p= 0. 000). Season also mediated the impact of the intervention in the Hills ( Odds Ratios= 1. 728 and 1. 333, p= 0. 000 and p= 0.001 of the
the
approximately 2. 2 times as an additional food group ( p< 0. 001), have achieved MDD ( p= 0. 015), and had
0. 503,
the
separately( Table 9).
words,
given
of on
Ratio=
during
difference- in-
of
coefficient
of
years
consumed
8). The impact the
among the treated children, in Table 9 are presented as
estimated effect
term
other
likelihood
Coefficients an
Table
the Terai
and
period,
estimated
regions(
vari-
outcome
women' s education
in the DDS, the likelihood
change
the
dietary and
by calculating
ATET. In
intervention for two
likely
one
or
the
size
interaction
the
average
intervention.
across
for the Hills
was
achieving MDD, in the previous the
household
estimated
Phase
model
that
revealed
with
they differ
intervention
the
the
analysis
associated
difference- in- differences
and
in
the
Terai
for
1. 049, p= 0. 826
DDS
or
for
and p= 0. 259
MDD ( Odds
for DDS
and
MDD, respectively). This indicated that the intervention was more effective at improving child dietary quality during the hungry season than in the harvest season in the Hills, but not the Terai. Differ-
ences in program effects across seasons may have occurred because it may be easier to see an effect during the hungry season, since the baseline status quo is worse. In other words, it' s easier to see program benefits where conditions were worse to begin with,
because there are likely to be diminishing
marginal returns to com-
munity development activities. In general, child- level variables were not associated with diet-
ary outcomes, as perhaps foreshadowed by the t- tests in preliminary analysis. Results did not change when including or
excluding the youngest children( aged 6- 12 months) whose diets differed the
most
from the
rest of
the group,
from the
analysis.
A. F.
Darrouzet- Nardi
et al./
Food
Table 5
61(
Policy
2016) 185-
197
193
across the three intervention in
Difference
for
t- tests)
means(
dietary
outcomes
across
age,
gender,
season,
and
levels ( zero exposure, one year of
exposure, two years of exposure). The results of the ANCOVA indi-
region.
cated that there was a significant effect of the amount of the interDDS
MDD
ASF
vention
Girls
3. 86
0. 79
0. 62
Boys
3. 84
0. 78
0. 61
0. 02
0. 01
0. 01
0. 31
0. 11
0. 23
Difference Pr( T>
t)
Pr( T<
or
t)
the intervention
Age 6
12
mos.-
12
Age>
mos.
mos.
Difference Pr( T>
t)
Pr( T<
t)
0. 000), 1. 12 times as likelyto have achieved MDD
p
0. 72
0. 47
0. 97
0. 63
tion for only one year. There were no measurable
0. 15
intervention ANCOVA
0. 25
0. 00"'
0. 000'
0. 00"'
on dietary
in Table
quality
3. 67
0. 55
0. 59
Harvest
season
4. 13
0. 74
0. 61
Difference Pr( T>
t)
Pr( T<
or
0.00-
t)
region
Hills
the intervention
region
t)
Pr( T>
0. 00-
t)
Pr( T<
Two-
DDS=
Dietary Diversity Score. Minimum dietary diversity.
t-test
sample
Animal
Source
with
Foods
equal
to
zero.
These
0. 82
0. 59
3. 81
0. 80
0. 65
The
0. 06
estimated
0. 02
0. 05*
Notes:
equal
0. 05*
0. 00"'
magnitudes
of these
results
analysis odds
lend
further
for all the
ratios
are
and statistically
support
dietary
smaller
than
to
Just
what
as
with
the
statistical
difference- in- differences
model
power.
presented
above, we can aggregate the ANCOVA for the whole sample to
show
generalizability ( Table 12). In this specification, that children who had received the intervention
years were approximately an additional that
appears
boy
children
compared on
1980s
and
South
Asia
1990s
while
others
did
is bias
If there
allocation
marriage
displacing
nization
1997;
against
evidence
Messer,
girl
1997;
Miller,
out
Gittelsohn
Gupta, 1987),
1997),
due to
agricultural
mecha-
results
Gittelsohn
et
al.,
potential
The literature
1997; Messer, 1997).
any disparities in how girls and boys were affected Heifer intervention over time longer periods of time. below
10
this
specification,
p= 0. 001), p= 0. 001),
have
to
likely
as
the
shows
1. 15
and
results
years
were
an
for the
that
show
consumed
times
1. 18
pooled
results
intervention for two
the
received
of
it is difficult to quantify cultural beliefs 1997), and further work would be needed to
Messer,
traditions(
et
by
times
had received significance
the intervention of the model
for only one year. F- tests for joint
indicate
that we can reject the null
hypothesis that the coefficients on all of the variables in the model are equal to zero.
In summary, there are four main results to emphasize. The first seasons,
for children aged 6 months to 8 years, and this variation
this
even using just dietary diversity
as an indicator.
The second result is that a community- level, nutrition- sensitive intervention
without an explicit nutrition
focus had a significant
impact on child dietary quality in rural Nepal. The third result is that this intervention was effective at improving DDS, MDD, and ASF in the Hills, which is arguably the more agro- ecologically vulnerable region of Nepal when compared with the Terai. The
sample
children
as
who
a
had
approximately 1. 52 food group
additional
to have likely as likely to have
as
have achieved MDD ( p= 0.072), and 1. 09 times as likely to have consumed an animal sourced food ( p= 0.001) as children in who
is measurable
assess
In
1997),
that
exemplifies
1. 12 times as likely to have consumed
food group ( p= 0. 034), and 1. 04 times as likely to
pregnancy4
foods during menstruation and 1997), or lower perceived economic
Gittelsohn
children ( area
al.,
for two
result is that child dietary quality in rural Nepal varies with the
of certain
restrictions
Table
bias, et al.,
labor force ( Miller,
the
of
foods in
of
of gender
in the intrahousehold
children
subconscious (
practices ( women
distributions
found
studies
foods, it may be
of
traditional
some
Miller,
not(
may have slightly improved dietary girl children. Evidence from the
with
intrahousehold
the
was mixed:
was
significant effect of the intervention
address
quality indicators
the
outcomes.
model. Still, there is
ing the multiple survey rounds while optimizing
consumption.
01.
times
F- tests for
in the Hills. The comparison of the two models is useful for exploit-
p<. 10.
whole.
of interest.
with the difference- in- differences
a measureable
variances.
p<. 05.
and
outcomes
h Yp othesis that the coefficients on all of the variables in the model
0.0. 111111
3. 88
0. 07
or
on the dietary
difference- in- differences
Difference
in this
from
11 show that we can reject the null hypothesis
joint significance of the model indicate that we can reject the null
are
Terai
girl
effects of the
The results
0. 19
0. 46
Region
1997).
in the Terai.
that there is no statistically significant effect of different levels of season
It
p= 0.002),
3. 88
0.82
or
in the Hills for two years were approximately
3. 05
Hungry
p<.
In
and 1. 20 times as likely to have consumed an animal sourced food p< 0.001) as children in the Hills who had received the interven-
Season
ASF=
on child dietary quality( Table 11).
1. 36 times as likely to have consumed an additional food group
Age
MDD=
had been received
this specification, results show that children who had received
Gender
MDD
achieved
consumed
fourth result is that the intervention
had a stronger
effect during
the hungry season, arguably when it was needed most. The use of an alternate model for comparison, ANCOVA, demonstrates
that
effect sizes may in fact be much smaller than those estimated
by
difference- in- differences.
ASF
p= 0.006) as children who had received the intervention for only The
one year.
magnitude
was estimated to
of
be dismissed
from
To
the
address
we
ANCOVA). effects
of
compared
The the
odds
ratios are smaller
than
what
into
estimate results
purpose
of
intervention
using
this
on
was
DDS,
an
to
MDD
Discussion
but are not small enough
a country- level policy- making standpoint. loss in power that comes with pooling
difference- in- differences groups,
these
for the regions separately,
baseline analysis
determine and
ASF
and of
Children in the Hills experienced a
endline
covariance
whether were
the
different
odds of consuming
This
causal
mechanism
would
not
fit for
our
study
population
per
se
due
to the
ages of the children included in the study( not old enough to be menstruating yet). However, girls
and
the
presence
women
in
of
general.
this
cultural
practice
may
be indicative
of views
towards
DDS and improved
This was
a community- level, nutrition- sensitive program without a specific focus on child dietary improvement. The main mechanism through which the intervention
functioned
is still unclear, but could relate
to the improvement to livestock holdings or women' s empower-
ment. The increase 4
improved
ASF and MDD with the intervention.
in the number of households
owning
goats
and poultry over the study period, as well as the promotion of kitchen gardens, may have provided increased income or direct nutritional benefit through home consumption. The intervention' s emphasis
on
social
capital
and
community development
may
also
194
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
Table
6
Dietary quality indicators for children at baseline, by child age and sex groupings. Sub-
sample
N
of children
score(
6-
12
boys
Minimum
Dietary diversity mean)
of
78
with
MDD)
0
2.
girls
and
boys
45
3. 62
53. 3
73. 3
19- 24
month-
old
girls
and
boys
26
3. 81
57. 7
43. 8
25- 36
month-
old
girls
and
boys
26
3. 49
48.8
48. 8
37- 60
month-
old
girls
and
boys
84
3. 72
58. 6
64. 8
162
3. 59
49.8
56. 3
60
old
old
month-
girls
girls
and
and
boys
All
girls
291
3. 86
62.
8
59. 7
All
boys
298
3. 84
61. 6
58. 9
589
3. 57
50. 7
57. 9
Total
foods
43. 9
41
old
month-
18
source
of children with ASF)
month-
13-
22.
Animal
dietary diversity
children
Table 7
Percentage of children consuming particular foods, at each survey point. Observation
N
Starchy
Oil
staple
Dal
Milk
Meat
Eggs
Vit.
A
rich
foods
Other fruits and vegetables
Baseline
589
95. 8
93. 5
43. 0
18. 8
41. 4
93
8. 8
6-
524
99. 0
94. 3
53. 4
20. 4
54. 4
8. 6
13. 2
72. 9
months
445
98. 7
85. 6
51. 5
14.
2
40. 7
13. 5
6. 7
33. 5
months
523
97. 3
94.1
61. 8
15. 1
40.2
8. 0
8. 2
74.4
months
533
98. 5
96. 8
55. 5
143
503
9. 2
11. 8
54.4
months
12-
1824
Table 8
37. 9
advantage of the Heifer intervention more effectively. This may
Exploratory
regression.
Variable
have occurred because the Hills has more land available for grazing Units
1)
2)
(
DDS Exposure
Years
to
Terai
-
0. 560) 0. 408"
Binary
region
(
income
Annual
Nepali
rupees
per
(
0. 000
-
ASF
these rainfed grazing lands( Metz, 1989; LRMP, 1986). In contrast,
0. 085
-
0. 074
lower elevations such as the Terai are characterized by fewer live-
0. 195)
(
0.287)
stock which live and graze closer people' s homes, due to higher
0. 232-
0. 036)
than the Terai, and livestock are more mobile to take advantage of
3)
MDD
0. 100
intervention
(
human population pressure and the larger quantity of irrigated
0. 085
0.002) 0. 000
( -
0.276) 0. 000
0. 547) livestock
FAO
score
Number
size
0. 086
units
of people
s
education
-
Years
Months
age
age2
Child
constant
Number
population pressure in the Terai, or larger mean household size,
0. 014
which might make it more challenging for community- level devel-
(
0. 308)
0. 198***
0.044'
-
(
(
0.051)
(
0. 006
-
0.899)
(
0.300)
0. 000
-
0. 000
(
0. 201 0. 163)
0.625) 0. 000
0.249)
(
0.668) 0. 002
(
0. 000)
464
throughout the year. Wheat, which accounts for just 19% of Nepal' s
cereal production, is harvested in Nepal approximately from March to June( FAO, 2007). Maize, millet, and rice, which together account
from August to November. Other studies have found variation
dietary income
least
squares.
p-
values
results of this study indicate that a community- level, nutrition-
463
in
in
patterns and nutritional status across seasons in lowcountries ( Savy et al., 2006; Mitchikpe et al., 2009). The
sensitive
estimated
members.
Season was an important predictor in both regions, presumably because cereal harvests in Nepal are not uniformly distributed
for 80% of Nepal' s cereal production, are harvested approximately
0.498) 0. 545-
(
opment activities to succeed there, or to allocate program benefits
among more household
0.263) 0. 020
( -
0. 623)
(
0. 257)
0.026
0. 004
461
by ordinary Standard errors are clustered by family. regression
analytical models with the household fixed- effects. The differential
impacts across regions may also be due to the higher relative
observations
A linear
These
into the
-
2. 873'#
of
the Terai.
at baseline are incorporated
0. 012
0. 000)
N
in mind, the Hills
0. 047' -
0. 607) constant
than
0.240)
0. 004
Months2
0. 025
livestock
(
0. 498) Child
to raising
0.237)
0. 072
Binary
0. 717)
(
0. 024
0. 001) ( Sex
conducive
(
0. 061) women'
0. 984)
(
0. 138) Household
are more
time- invariant differences
year
Animal
cropland ( Metz, 1989). With these differences
intervention
such as Heifer may ameliorate
some of the
seasonal fluctuations in food availability. As described by Ruel parentheses;
and Alderman(
2013), nutrition- sensitive programs can be helpful
p<.
10.
templates
for scale- up at the regional
p<.
05.
adapted to be nutrition- specific programs.
or national
level, or be
p<. 0. Strengths and limitations
have improved child dietary quality, and the pathway through this
which
from
may have occurred is through women' in Heifer' s Self- Help Groups.
The
impact in the Hills
positive
baseline dietary
was
achieve
a
short
period
of
animal
also
initially
quality great improvement
could
mean
s empowerment
time. It
scores
in
is
also
the
may have occurred because low that the intervention
so
in dietary quality in a relatively that the higher baseline
possible
Hills
allowed
households
The strengths of this study include the random assignment across villages which allows for valid comparison of the program' s
participation
to
take
effects between implementation
Group 1 and Group 2, the semi- annual
survey
which allows for the analysis of seasonal patterns
in dietary quality, the inclusion of older children up to age 8, which is a rare occurrence in dietary quality studies, and the individuallevel 24 h diet diversity recall data. Household fixed- effects can
A. F.
Darrouzet- Nardi
et al./
Food
Policy
2016) 185- 197
61(
195
Table 9
Difference- in- differences, by region. Outcome
Units
region
Intervention
1)
Years
Phase
2)
3)
4)
5)
6)
DDS Terai
DDS Hills
MDD Terai
MDD Hills
ASF Terai
ASF Hills
1. 171
0. 381***
1. 048
0. 859
0. 958
0. 706-
0. 333)
0. 000)
043
0. 429"""
Binary
1.
Interaction
1. 190
Binary
0.836
Interaction
0. 981
0. 750)
0. 550)
035
1.
0. 000)
0. 128)
686"""
0.
0. 602)
0. 592)
0. 001)
0.810-
0. 994
0. 000)
0. 924)
0. 018)
2700"
Intervention*
phase
2. 197"""
0. 211)
1. 065
0. 000)
1.
0380)
1. 062
0. 015)
1. 380"""
0. 415)
0. 001)
8790"
Hungry
season
0. 291***
0. 118) Intervention*
season
0. 000)
child
Binary
1. 060"
Months
1. 001
Months2
1.
0. 974
age
0. 787) 2
Child
age)
N
0. 504)
0. 690) 0. 992
0. 030) 1.
0. 687)
000
1. 001
0. 792)
000
1.
0. 402)
1632
1. 029
1. 042""
0. 480) 1.
0. 639)
0. 771)
0. 604)
000
0.968
1. 014
1. 001
0. 668)
966
0. 963
0. 990
0374) 1.
0. 391)
1618
0. 001)
1. 001
1. 000
0. 621)
049
0. 259)
0. 075)
003
0. 400)
000
0. 000) 1. 222"""
1. 027"
0. 524) 1.
0. 613'""
0. 025) 1.
0. 000)
0. 068)
Child
728"""
1.
0. 826)
Boy
0.
0. 776)
000
1. 000
0. 625)
972
0. 659)
1619
969
The estimated coefficients on Intervention* Phase is the average treatment effect on the treated of the intervention. Group 1, having received the intervention starting one year earlier than Group 2, had longer durations for the" Intervention" variable. Coefficients are reported as odds ratios; p- values in parentheses; Standard errors are clustered by household; household fixed- effects not shown.
p<. 10. p<. 05. p<. 01.
Table 10
villages self- selected into assessment in- differences for
Difference-
the
sample
as
a whole.
Units
1)
Years
MDD
0. 757'
0. 960
0. 058) Phase
0. 736"
Binary
Interaction
phase
(
1. 524"""
Interaction
season
1.
Boy
1.
Binary
child
013
Child
Child
2
Months2
1.
age)
(
(
0. 632)
(
(
015
Generalizability
indica-
et al.,
of results
As with any impact
(
evaluation,
external
validity
of results
is
important to consider. For comparison and to inform the potential
generalizability of this study, the median household size in Nepal is
0. 883) 1.
0. 657)
in nutritional
animals ( Rawlins
programming activities.
0. 255)
000
1.
from donated
2014). This study focused on quantifying the other aspects of Heifer
1. 000
0. 508)
000
tors which come directly
0. 706)
1. 001
0. 993)
of Heifer projects have found improvements
18o""
1. 017
0. 508)
1. 000
Months
age
(
(
008
1.
0. 622)
1.
0. 001)
resources
0. 508)
1. 117""" (
over
observation point, to elucidate causal mechanisms. Other studies
0. 006)
(
or control
measurement of socioeconomic status and animal holdings at each
0. 972
0.000)
(
229"""
0. 008)
(
0. 765***
0. 000) Intervention"
0. 021)
0. 558"""
Binary
season
(
was not measured. Further work is needed, including the detailed
1.
use, empowerment,
data
0. 852'"
0. 090)
1. 146-
0. 001)
Hungry
(
for impact, since detailed
on women' s time
0. 912"
0. 034)
to assess mechanisms
ASF
0. 012)
(
0. 889"'
0. 014) Intervention*
0. 523)
(
not possible
3)
2)
DDS Intervention
for eligibility for Heifer' s pro-
gramming, thus potentially limiting external validity. Lastly, it was
4. 5 members, and the median years of women' s educational attain-
000
ment
0. 544)
is
1. 15 years
International,
for
2012).
Terai
and
Hill
Other variables
regions
could
combined (
not be directly
ICF
com-
pared to national averages because the DHS reports income and N
2584
2604
2588
socioeconomic scores as quintiles. The FAO livestock index not is The
estimated
the treated
on
coefficients
Intervention*
Phase
is
the
average
treatment
effect
on
Group 1, having received the intervention starting one year earlier than Group 2, had longer durations for the" Intervention" variable. Coefficients are
clustered
p<.
10.
p<.
05.
measured
the intervention.
of
reported
are
as
ratios;
odds
p-
values
in
by household; household fixed- effects
Standard
parentheses; not
errors
stock (
but 78% of household
International,
Average
2012).
in Nepal
gross
own live-
national
income
per capita in Nepal was$ 2410( PPP) in 2011- 2015, which converts to about
shown.
for the DHS,
ICF
256, 336
Nepali
rupees
per year(
World
Bank,
2015).
The
GNI for Nepal as a whole is likely much larger than the income estimated in this study because the study population
p<. 01.
is predominantly
agricultural and consumes much of the own- production of food.
This intervention was administered
at the community- level, to
rural farming communities which met criteria for participation by control
for
inequalities present main
heterogeneity
unobservable within
and
affect
limitations
of
households results (
this
ipation intensity
was
measured
time
at
all
such
as
across
birth
Jayachandran
and
households,
order
bias
Pande,
could
2013).
study include that household- level
not
measured,
points
of
that
key
observation,
variables and
that
but
Heifer. Therefore, communities which would not have met their
be
criteria may not achieve similar results. The six communities were
The
diverse as a group( Tables 2- 4), and arguably large enough to rep-
partic-
were
not
included
resent rural farming communities Nepal.
Moreover,
across
the
study
in the Hills and Terai regions of
only participating period,
which
households is
a
significant
were
measured
limitation
to
196
A.F. Darrouzet- Nardi et al./ Food Policy 61( 2016) 185- 197
Table 11
Analysis of covariance( ANCOVA), stratified by region. Variable
Lagged
Units
1)
Lag
outcome
2)
3)
4)
5)
6)
DDS Terai
DDS Hills
MDD Terai
MDD Hills
ASF Terai
ASF Hills
1. 223'*
1. 052
1. 118-
0. 986
1. 100***
1. 059
0. 000)
0. 194)
0. 000)
0. 712)
0. 002)
0. 157)
0*
Intervention
Years
0.963
Binary
0. 940
Binary
0.639***
Binary
1. 357*
1. 360*
0. 550)
0. 987
0. 000)
1.
0. 638)
119*'
1. 196* 0*
0. 998
0. 002)
0. 941)
0. 000)
0*
Survey
round
2
Survey
round
3
Survey
round
4
3. 960*
0. 561)
0. 973
0. 000)
0. 565)
1. 003
0. 000)
0. 837`*
1. 064
0. 000)
1. 527*'*
0. 953)
0. 922
0. 689)
0. 000)
0. 208)
1. 354*
1. 116***
1. 142**
0. 016)
0. 008)
0. 012)
1. 3820. 000)
0.890*-
1. 169*
0. 022)
0. 026)
0*
0. 001)
0. 957
0. 930
0. 305)
0. 191)
N
1057
614
1071
622
1057
620
F- statistic
20.22
29. 35
10.
54
24. 15
3. 62
7.91
Prob>
0. 000
0. 000
0. 000
0. 000
0.003
0. 000
F
Note: Three survey round binary indicators instead of four( five minus one to prevent perfect collinearity) because the lagged dependent variable is perfectly collinear with the survey round binary indicators as well. The estimated coefficients on Intervention are the estimates of treatment impact. Coefficients are reported as odds ratios; p- values in parentheses.* p<. 10. p<. 05. p<. 01.
Table
12
randomized
Analysis
Covariance( ANCOVA) for
of
Variable
Lagged
Units
outcome
the
whole
(
sample.
1)
results, the analytical methods utilized here increase the external
1. o75***
1. o86***
validity of the study. Many impact evaluations are highly focused
Years
1. 117**
0. 002)
(
(
Survey
round
3
Binary
0. 738***
Survey
round
4
Binary
1. 317#**
(
near
with
the survey
Intervention ratios;
p-
are
the
in
values
the
1693 21.
0. 000
0. 000
as
well.
The
to the impairment
of external
of impact evaluations.
Conclusion
0. 585)
The results
0. 937*
(
minus
estimated are
suggest that the impact of interventions
to improve
status of children depends on the initial agroecological
conditions
in
the
geographic
region
concern,
child dietary quality, even when this outcome is not a specific goal
0. 000
of the program.
to
precolli-
coefficients
reported
as
on
odds
parentheses.
Our results demonstrate
through which community
tions can improve the collection
through
nutrition.
of longitudinal
affect
that there are multiple
and agricultural
interven-
Further work is needed, especially data, to investigate
which community- level development
as the one studied here operate. A potential
p<. 10.
may
that
7. 66
one
interventions
and
1677
pathways
nutrition- sensitive
of
community- level,
is perfectly
variable
nutritional
0.057)
78
impact. Coefficients
treatment
of
sometimes
between these two key characteristics
0.004)
(
four( five
of
lagged dependent
validity,
0. 978
0. 001)
1671
binary indicators
round
estimates
(
0. 000)
28. 14
binary indicators instead
collinearity) because
0.004)
1. 120-
(
on internal
validity. With this study design, we aimed to improve the balance
1. 124`*
0. 001)
(
0.000)
F
(
145-
0. 858***
0.001)
statistic
0. 001) 1. 070-
0. 072) 1.
572-*
0.000)
N
(
1. 041*
0.034)
round
participa-
1.
1.
perfect
to maximize
Lag
Binary
vent
attempt
endogenous
ASF
2
Note: Three survey
trials which
the potentially
MDD
165***
round
Prob>
field
DDS
Survey
F-
controlled
validity. Although
tion levels are a threat to internal validity and may have inflated
3)
2)
0. 000) Intervention
internal
the mechanisms
interventions key extension
such of this
study would be to collect data for and estimate the Women' s
p< os p<. 01.
Empowerment
in
Agriculture
Index (
Alkire
et
al.,
2013).
More
detailed measurement of micronutrient intake for children would
also be helpful to inform nutrition- sensitive programming. generalizability involvement
within in
communities,
community- level
if
there
intervention
is
endogenous If
activities.
every
household in all participating communities were measured regardless
of participation
attenuate.
up- take
levels in the Heifer programming,
However,
non- universal
of programming
participation
activities
more
and
could
results
This study was supported
endogenous
accurately
Sources of funding
reflects
and funded by Heifer International.
the Conflicts of interest
real- world.
We would expect better external validity for this interventionrandomized
and administered
at
the
community- level-
than
for
a
The authors do not have any conflict of interest to declare.
intervention which was randomized and administered at the individual or
household- level-
because
typically target communities the
expense
eligible
interventions ferent
and
logistical
participants such as
contexts,
for this
is less
a
national
policies
and programs
or groups and not individuals,
challenge
of means-
program.
Evaluation
one, which
common
than
could
be
testing and finding of broad, holistic
adapted
evaluations
of
to
many dif-
highly-
Authors' contributions
due to
specific
L.M., M. L., and N.J. designed the study. L.M., N.J., M. L., P. S., and S. M. supervised
tion activities. data
analysis,
the field work and data collection, and the interven-
L. M. managed A.D. N.
and
data cleaning;
L. M. drafted the
A. D. N. conducted
manuscript;
L.M.
the
and
B.
Darrouzet- Nardi
A. F.
R.
consulted
to the
on statistical
manuscript
and
development
model
all
authors
and
it for
approved
made
et al./
revisions
Food
Policy
2016) 185-
61(
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Approving
ethics
Rev. 1, 77- 100. R., 2013.
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Gupta, M. D., 1987. Selective discrimination against female children in rural Punjab, India. Popul.
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