Establishing integrated agriculture-nutrition programmes to diversify household food and diets in rural India
Establishing integrated agriculture-nutrition programmes to diversify household food and diets in rural India
A. V. Vijaya Bhaskar 0 1
D. J. Nithya 0 1
S. Raju 0 1
R. V. Bhavani 0 1
0 Research Programme on Leveraging Agriculture for Nutrition in South Asia (LANSA), M.S. Swaminathan Research Foundation (MSSRF) , Chennai, Tamilnadu 600 113 , India
1 Department of Ecological Plant Protection, University of Kassel , Nordbahnhofstr.1a, 37213 Witzenhausen , Germany
2 R. V. Bhavani
Agriculture is the predominant livelihood for 70 % of the population living in rural India, and food expenses occupy a major proportion of their household budget. Rural household diets suggest that agricultural growth has contributed to increasing calorie intake with very minimal effect on the intake of protein and micronutrients. This in turn causes weak positive impact of agriculture on household dietary diversity and nutrient adequacy. Given the prevalence of high levels of under-nutrition and a large population dependent on agriculture, recent thinking globally on leveraging agriculture for nutrition security has encouraged the agricultural sector to realign its focus not only to increase food production, but also to address under-nutrition. Against this background, an exploratory study was conducted in resource poor villages of Wardha and Koraput districts in the states of Maharashtra and Odisha in India, to investigate how location-specific Farming System for Nutrition (FSN) interventions can potentially improve the diversity of household diets and nutrition outcomes. A detailed baseline study was undertaken to identify the existing disconnect between agriculturenutrition linkages. In the study locations, the proportion of all forms of under-nutrition, vitamin A deficiency and iron-deficiency anaemia among children <5-years of age appeared unacceptably high. A high prevalence rate of chronic energy deficient (CED) women and anaemic pregnant women was also observed. A higher risk of under-nutrition and micronutrient deficiency among household members was associated with substandard living conditions of the surveyed households. Cropping systems in Wardha were primarily dominated by rain-fed commercial cash crops while rain-fed subsistence farming predominated in Koraput. Households in both study locations were found to have cereal-dominated diets with average daily consumption of pulses, fruits and vegetables, and milk and milk products well below the recommended daily intake level, indicating low dietary diversity. In both Wardha and Koraput, CED in adults (>18 years) significantly increased as the dietary diversity score (DDS) decreased from high to low. In Koraput, the prevalence rate of anaemia in adolescent girls and women significantly increased, as the DDS decreased. We conclude that food and diets lacking diversity and without nutrition-sensitive farming systems (either commercial- or subsistence-based) may not be appropriate to improve household nutrition and health status. Our findings provide a basis for structuring integrated agriculture-nutrition programmes or a FSN approach to diversifying household food and diets, for improving nutrition and health in India.
Farming system; Nutrition security; Koraput; Wardha; Dietary diversity; Household food security
Food grain production in India crossed 260 million tonnes
. However, in the same period,
about 190.7 million persons (15.2% of the total population)
living in rural areas remained chronically undernourished
(FAO, IFAD and WFP 2014)
. The National Family Health
Survey (NFHS-4) reported that among rural children under
age five, 41%, 21% and 38% are stunted, wasted and
. The latest Global
Nutrition Report highlighted that 48% of rural Indian women
in the reproductive age group are anaemic
figure stood even higher at 54% in NFHS-4
Despite recent significant gains in economic progress and
agricultural productivity, under-nutrition remains a challenge in
India. The terminal year of the UN Millennium Development
Goals (December 2015) saw India lagging in achieving the
target of reducing under-nutrition, while achieving the target
for reducing poverty
Three widely reported indicators for food and nutrition
insecurity at the household level are the unavailability of food,
inaccessibility of food produced, and the available or
accessible food does not ensure a balanced diet
(Das et al. 2014;
Masset et al. 2011)
. Agriculture remains an important focus
for pro-poor and pro-rural nutritional interventions in India.
Almost 69% of the population live in rural areas according to
Census 2011 (Chandramouli 2011) and more than half the
workforce are engaged in agriculture and allied activities.
This makes leveraging agriculture to address under-nutrition
a key area of focus. Increased food production certainly
improves food availability, but by itself does little to ensure that
poor and vulnerable people have access to the food produced;
neither does it provide information related to the quality and
enrichment of the food that is produced
(World Bank 2007)
There is also evidence that increased income does not
necessarily address a shift in diet preferences
(Global Panel 2015;
World Bank 2007)
. The problem of under-nutrition therefore
has to be dealt with by addressing compounding factors that
include nutrition-sensitive agriculture, increasing incomes,
improving food accessibility, shifting dietary patterns,
nutrition education and health awareness.
Evidence is found in the literature of the different pathways
linking agriculture and nutrition
(World Bank 2007; FAO
2013; Kadiyala et al. 2014; Kadiyala et al. 2016; Gillespie
and van den Bold 2017)
. Taking into account the spatial
influence of farming practices, cultural settings, resource
availability at a household level, and soil and agro-ecological
environment, what may be considered a fitting strategy at one
place, while providing the framework, is unlikely to be
directly applicable in a different setting. Led by the M.S.
Swaminathan Research Foundation (MSSRF), the research
programme on Leveraging Agriculture for Nutrition in
South Asia (LANSA) seeks evidence on ‘How agricultural
interventions can be pro-nutrition?’ Farming System for
Nutrition (FSN), as defined by M.S. Swaminathan, envisages
‘the introduction of location-specific agricultural remedies for
nutritional maladies by mainstreaming nutritional criteria in
the selection of farm-household system components involving
crops, animals and, wherever feasible, fish’
(Das et al. 2014;
Nagarajan et al. 2014)
. As suggested by Varian (1992), FSN
includes a set of ‘agricultural curatives’ (the combination of
available farm resources including improved seeds, soil
technology, bio-fortification, setting up small-scale fisheries,
poultry development, animal husbandry, homestead and
community nutrition gardening) as inputs to raise income and
improve nutrition. The underlying hypothesis is that
nutritional outcomes and dietary diversification in a rural population
improves through agricultural production for consumption
(direct) or by production for sale (indirect)
. In general, a diet is the composition of the food basket
consumed by the household. An improvement in diet can be
the outcome of diversification into non-staple foods and/or
enrichment with items from among regularly consumed staple
(Masset et al. 2011)
A systematic exploratory study was initiated in selected
resource-poor villages of Wardha district in the state of
Maharashtra and Koraput district in the state of Odisha to
investigate how location-specific FSN interventions can
improve household diet and nutrition outcomes. To establish
integrated agriculture-nutrition programmes, it is important
to understand the underlying causes that limit food and
nutrition security in a household. Baseline information provides a
reference point for monitoring and evaluation of the progress
and effectiveness of the integrated agriculture-nutrition
programmes. It provides the starting point for effective
structuring of activities related to FSN interventions. In addition,
the baseline study gathers the information to be used in
subsequent assessments of how efficiently the activity is being
implemented and the ultimate results of the activity, and forms
a basis for ensuring accountability to the rural households who
are at risk of under-nutrition.
The present study is one of the first to systematically unfold
agriculture, nutrition and health complexities in districts with
a high burden of under-nutrition in India. As seen in other
(Cole et al. 2016; Jolley 2014;
, the agriculture, nutrition and health sectors
in India largely operate in separate ‘silos’, administratively
governed by different Ministries and professionally by
separate scientific and expert workforces
(Nagarajan et al. 2014)
This situation has resulted in an extended gap between
agriculture and health. The role of food, access to food and
balanced diet that is so crucial for human well-being has emerged
as a major concern
(Nagarajan et al. 2014)
agricultural policy support has done little to protect farmers against
risks including those from climate change and pressure of
population on land, or to promote rural prosperity.
Agricultural policy in India has focused primarily on
strengthening the production of staple food crops, especially rice and
wheat, through price incentives and the promotion of farm
(Das et al. 2014)
. This approach, while
addressing food security, has led to the neglect of several
naturallyfortified food crops and crop diversification, contributing to
soil impoverishment and limiting dietary diversity.
Thus in rural India, farmers and landless agricultural and
non-agricultural labourers are disregarded, both economically
and agriculturally, and from nutrition and health perspectives.
The selected districts for this study, Wardha and Koraput, are
classic examples of such marginalisation. Agriculture is the
primary occupation of the population in both of the study
locations, implying that better agriculture could be a potential
solution to combat nutrition and health inadequacies. Recent
studies have documented that changes in climate and
continuous repetitive cropping patterns over many years have
resulted in stagnant or reduced yields in these locations and across
many other Indian rural settings
(Nayak 2016; Talule 2015;
Udmale et al. 2015; Wani et al. 2016)
. Livelihood risk and
vulnerability has increased due to deteriorating cost/benefit
ratios. Agrarian crises and farmer suicide has been extensively
documented in Wardha
(Sontakke 2015; Kulkarni et al. 2016)
while Koraput is an agro-biodiversity hotspot, threatened by
erosion of natural resources and food insecurity
et al. 2015)
Holistic and integrated situational analyses will help to
identify the root causes of agricultural and nutrition
deficiencies among rural households; and also bring together
stakeholders to work together with farmers to seek solutions for
households and for policy makers. Pro-nutrition agriculture
allows for the testing of some promising crops such as
biofortified zinc- and iron-rich wheat
(Singh and Velu 2017;
Rosado et al. 2009)
, orange-fleshed sweet potato
et al. 2015; Borrill et al. 2014)
, and quality-protein maize
(Akalu et al. 2010; Gunaratna et al. 2010)
, along with soil
improving cropping strategies, with farmers’ involvement in
farm environments. Studies with these key crops reportedly
produced beneficial results for improved nutrition and
provided higher price margins. Like elsewhere, adopting key crops
within a FSN approach has the highest expectation in
promoting nutrition and food security in the selected study villages.
Overall, the strategic framework developed as a part of this
investigation will deliver valuable insights into the planning
and execution of multi-sectoral interventions to address
multidimensional problems with links between agriculture,
nutrition and health.
about the study intervention areas. Based on this, eight
villages comprising 822 households with a population of 3287 in
Wardha and eleven villages with 921 households and a
population of 3958 in Koraput were identified for the baseline
study and subsequent planning of integrated
2.2 Data collection instruments
Experienced field investigators (including enumerators) and
survey teams (including qualified phlebotomists) were
selected, re-trained and standardized in the survey methodology by
former and current scientists of the National Institute of
Nutrition (NIN), Hyderabad, India, before initiation of the
survey. The training took place over two weeks and covered
all the techniques of investigation that were used. To collect
reliable information, the field investigators and survey teams
committed substantial time to build rapport with the rural
householders in both study areas, to ensure good working
relationships. Participating households were made fully aware
of the need for baseline information for advancing FSN
interventions. The approach allowed the conduct of multiple
surveys from June 2013 to September 2014 to collect the
information described in the next sections.
2.2.1 Socio-demographic characteristics
A socio-demographic questionnaire elicited household
demographic and socio-economic information. The questionnaire
included questions on caste, age, gender, family size,
education and occupation of household heads, size of agricultural
land owned and preferred Kharif (June to October) and Rabi
(November to March) agricultural season crops, livestock
holdings, traditional homestead gardening and the types and
mix of horticultural crops. Other questions included type of
dwelling, fuel used for cooking, type of toilet, and the sources
of drinking water. Additional questions included the types of
food bought in the household, their source, monthly
expenditure on food, and who makes decisions on the amount of
money spent on food, which in turn impacts on household
food and diets.
2.1 Description of the study locations
2.2.2 Anthropometric measurements
The FSN study locations were purposively selected on the
basis of agro-climatic and socio-economic status, landholding
pattern, farming practices and food consumption pattern.
More information on the study locations has been reported
Das et al. (2014)
Nagarajan et al. (2014)
. Despite soil
and agro-ecological differences between the study areas, both
are characterized by rain-fed farming and by high levels of
under-nutrition. The Government of India’s Census data for
2011 provided preliminary socio-demographic information
The height and weight of all the household members in both
study areas were measured using standard equipment (Seco
weight balance, stadiometer and infantometer). The percent
distribution of preschool children according to underweight
(weight-for-age Z-score (WAZ) at least two standard
deviations (SD) below the median), stunted (height-for-age
Z-score (HAZ) at least 2SD below the median) and wasted
(weight-for-height (WHZ) Z-score at least 2SD below the
median) was determined based on the World Health Organization
child growth standards
. WHO Anthro (version
3.2.2, 2011) and Anthroplus (2007) software were used to
calculate the Z-scores. School-age children and adolescents
were categorized according to age/sex specific Body Mass
Index (BMI) recommended by the WHO (BMI Z-score
(BMIZ) at least 2SD below the median) classification; adult
nutritional status was categorized by BMI according to WHO
cut off levels for Asians (Chronic Energy Deficiency (CED)
2.2.3 Biochemical analysis
At both the locations, finger prick blood samples were
obtained for biochemical analysis from households having children
in the age group of 1–5 years, adolescent girls in the age group
of 12–17 years and women in the age group of 18–45 years.
The blood sample of children was tested for serum vitamin A
and haemoglobin (Hb). For adolescent girls and women, the
analysis was limited to haemoglobin. The blood samples were
collected using a filter paper technique to estimate the
haemoglobin levels by the cyanmethaemoglobin method
(Drabkin’s method) and blood vitamin A levels by dried blood
s p o t t e c h n i q u e u s i n g H i g h P e r f o r m a n c e L i q u i d
Chromatography (HPLC). The collected samples were
analysed at the NIN. The WHO cut off levels were used to
diagnose the extent and degree of iron-deficiency anaemia
(anaemic: Hb < 11 g/dl for children in the age 1–5 years and
pregnant women; Hb < 12 g/dl for girls in the age 12 to
45 years and lactating and non-pregnant non-lactating
women) and vitamin A deficiency (VAD) (blood vitamin
A < 20 μg/dl).
2.2.4 Food consumption pattern
A one-day 24-h diet recall method of an intra-household diet
survey was administered on a selected sub-sample of 300
households in Wardha and 300 in Koraput. A 24-h diet recall
method was performed continuously over a period of time to
capture food intake patterns on all days including Sunday,
given the general habit of consuming animal-sourced food
on holidays. The main criterion for sub-sampling included
households with children in the age group of 1–5 years. This
was to ensure we obtained information on food intake and
biochemical analysis for the same set of households. In case
households did not have children in this category, households
with adolescent girls in the age group of 12–17 years whose
blood haemoglobin levels had been analysed were included,
to obtain a total of 300 households following purposive
sampling. The mean intakes of food were compared with the
suggested balanced diet provided in ‘Recommended Dietary
Intakes for Indians’ (RDI) by the Indian Council of Medical
. In addition, it was presumed that a
household should consume by reference at least 70% of the
RDI. Using this reference, the frequency distribution (%) of
households according to a level of food intake of less than
70% of RDI was estimated. However, out of the thirteen food
groups studied (listed in the next section), nuts and oil seeds,
condiments and spices, fish and other sea foods, and meat and
poultry were not used for this calculation as there was no
2.2.5 Dietary diversity
Dietary diversity is a qualitative measure of food consumption
reflecting household access to a variety of foods, and is also a
proxy for nutrient adequacy of the diet of individuals
et al. 2007)
. The dietary diversity score (DDS) was estimated
using 24-h diet recall data for each person based on thirteen
food groups as recommended by
. The groups
included (1) cereals and millets, (2) pulses and legumes, (3)
green leafy vegetables, (4) roots and tubers, (5) other
vegetables, (6) nuts and oil seeds, (7) condiments and spices, (8)
fruits, (9) fish and other sea foods, (10) meat and poultry,
(11) milk and milk products, (12) fat and edible oils, and
(13) sugars and jaggery. The variable DDS was calculated
by summing the number of food groups consumed by the
household with the scores ranging from 1 to 13 as given by
. This was done after creating food group
variables for those food groups that needed to be aggregated.
The maximum and ideal score would be a DDS of 13 since
this would mean that the individual had consumed from each
of the 13 food groups at least once. The calculated DDS were
further categorized into tertiles: low (1 to 7), medium (8), and
high (9 to 13) dietary diversity based on the score distribution
within the population.
2.3 Statistical analysis
In addition to descriptive statistics, Pearson’s chi-square test
was conducted to determine the association of some
household socio-demographic variables with nutritional status of
individuals, and the association of nutrition status with DDS.
Statistical Package for Social Sciences (SPSS) software
version 20.0 was used to perform descriptive statistics and the
chi-square test. Significance level was fixed at 0.05.
Following a chi-square test, student’s t-test (two-group mean
comparison test using Stata software, version 12.0) was
performed to help further understand the relationship of
statistically significant variables. The majority of the population in a
category was considered as a base reference while making the
comparison. In our study with a large sample size, the data
distribution appeared highly skewed, indicating extremely
large variation within the group. A multivariate analysis that
attempted to control socio-demographic variables yielded
non-significant results. Hence a bi-variate analysis was
performed to better understand the relationships, as suggested
O’ Donnell et al. (2008
3.1 Socio-demographic status and farming practices
of the study population
Indigenous tribal communities, classified as Scheduled Tribes
under the Constitution of India, constituted the majority
(46.3%) of the human population in the selected villages we
studied. As high as 53.8% of total rural households in the
study areas lived in kutcha houses and the remaining 46.2%
in semi-pucca houses.1 A majority of households (59.7%)
were nuclear (with 1–4 members) and 37% had 5–7 members
(extended nuclear families). On the basis of age classification,
40.8% of the rural population were in the working age group
of 18–44 years, 25.4% were above 45 years and a small
percentage of between 10 and 12% were in the age groups of 12–
17, 6–11 and 0–5 years, respectively. Table 1 gives the
sociodemographic characteristics of the study villages.
In terms of sanitation conditions, nearly 52% of households
in Wardha had access to piped water for drinking whilst 66%
of households in Koraput sourced it from a tube-well. Almost
all (98%) of the households used wood as fuel for cooking.
Most households (89%) practiced open defecation. However,
in Wardha 22% of households had a sanitary latrine facility, in
contrast to only 1.2% in Koraput.
In Koraput, most (66%) household heads had no formal
education; the corresponding figure was 22% in Wardha.
About 56.8% of household heads were cultivators, 26%
agricultural wage labours and 17.5% other casual labour/daily
wage earners. Based on the total landholding size, the
Agriculture Census of India2 categorises farm-households
with an agricultural land area of less than 1 ha as marginal
farmers; those cultivating a land area of more than 1 ha but
less than 2 ha as small farmers; and those cultivating more
than 2 ha but less than 4 ha and more than 4 ha of land area as
semi-medium and medium farmers respectively. Households
not holding agricultural land are classified as landless. On the
basis of this classification, in Koraput 80.7% of the
farmhouseholds were marginal farmers, 16.6% were landless and
a very small proportion, 2.2% and 0.5% of farm-households
respectively were small and semi-medium farmers. In
contrast, in Wardha, about 37.2% households reported being
landless and 10.1% were marginal farmers; small and
semi1 A kutcha house is a house with a wall or roof made from mud, thatch, straw,
dry leaves or reeds. A semi-pucca house is a house with either the wall or roof
made of pucca materials such as burnt bricks, cement, concrete or tiles.
(Census of India definition, Retrieved: http://shodhganga.inflibnet.ac.in/
2 Retrived: http://agcensus.nic.in/document/agcensus2010/agcen2010rep.htm
medium farmers accounted for 25.9% and 18.9% of farm
households respectively. In Koraput, 71% of the households
reported to have farm animals (single or combination of small
ruminants, milch animals, draught animals and poultry) in
contrast to 55% in Wardha.
Considerable variation was observed between Wardha and
Koraput, in the number of households practicing traditional
homestead gardening and the size of allocated backyard land.
In Koraput, 48% of the households practiced traditional
homestead gardening while only 15% did in Wardha. Among
traditional gardening households in Wardha, the reported
available backyard land area per household on an average was
2.43 ± 6.07 (mean ± SD) m2. Irrespective of seasons, the types
of horticultural crops cultivated included beans, brinjal,
papaya, guava, lemon, bitter gourd, custard apple and green
chillies. Very limited cultivation of spinach, tomato, radish, carrot,
onion and pumpkin was reported. In general, about 50% of
traditional gardening households grew only one type of
horticulture crop, 30.7% grew two types and only 11.3% and 10%
reported three and four or more types and a mix of
horticultural crops. In Koraput, traditional home gardening
households reported an average 6.88 ± 3.24 (mean ± SD) m2 of
available backyard land per household. Most households grew
broad bean, tomato, brinjal, onion, green chillies, amaranths,
cauliflower, radish, spine gourd, cabbage, field bean, garlic
and papaya. Very limited bottle gourd, mustard, spinach, and
ginger was reported. In general, about 34.5% of traditional
gardening households grew two types and a mix of
horticultural crops, 25.6% one type and only 20.9% and 19% reported
three and four or more types and mix of horticultural crops.
Nevertheless, despite having backyard space, 67% of the total
population did not practice home gardening.
In the majority of households, the husband and wife (74%)
jointly made the decision on how much money was spent on
food and the types of food to be purchased. In Koraput, 31%
of households spent less than 1000 Indian rupees (Rs.) (~US
$15.44) per month on food items. About 55% of households
spent Rs. 1000 to less than Rs. 2000, and only a small
percentage of households (14%) spent Rs. 2000 or more on food
items. In contrast, 41.1% of households in Wardha spent Rs.
2000 to less than Rs. 3000 on food items, 38.3% spent Rs.
1000 to less than Rs. 2000 and a very small percentage of
4.3% spent less than Rs. 1000.
For crop types in Wardha, from the total of 822 households,
62.8% of households cultivated Kharif season crops
(rainfed). The percentage was derived using total households by
total landholders. Among Kharif growers, 34.5% of
farmhouseholds strip-cropped Bt-cotton with pigeon pea (Fig. 1).
Typically, Bt-cotton + pigeon pea occupied most of the land
area, 26.5% of households additionally used some proportion
of land area to cultivate soybean and 22% sorghum (mainly
for fodder). The remaining households (17%) reported sole
cropping mostly soybean, desi cotton, pigeon pea or sorghum.
Socio-demographic characteristics of the study villages in Wardha and Koraput in India
Demographic and socio-economic characteristics
*N indicates the total number of households, except for gender and age group, where N indicates the total population. Figures in parenthesis indicate
Among the 62.8% of households cultivating in the Kharif,
only 14.9% also cultivated in the Rabi (cool dry) season.
The Rabi land area was mostly occupied with sole-crop wheat
(54.6%), wheat intercropped with chick pea (32.5%) and sole
chick pea (13%).
With respect to crop types in Koraput, of the 921
households, 83.4% of households cultivated Kharif season crops.
Among Kharif growers, about 64.5% of farm-households
cultivated rice (Fig. 2). Rice systems occupied most of the
land, while some (30.5%) households additionally cultivated
a portion of upland area with finger millet or little millet. A
very small percentage of farm-households (5%) cultivated
sole-crop or mixtures of horse gram, finger millet or little
millet. Of the 83.4% households cultivating during the
Kharif, only 23.3% households cultivated Rabi season crops.
Rabi land area was predominately occupied with groundnut
Cotton + Cotton +
Wheat + chick Chick pea
(41.3%), green gram (23%), maize (17.3%), finger millet
(11.7%) and black gram (6.7%).
3.2 Anthropometric and biochemical measurements
In both locations, more than 40% of children under age five
were reported underweight (WAZ < −2SD), 35% stunted
(HAZ < −2SD) and about 27% wasted (WHZ < −2SD). In
Koraput, 41.1% of school-age children (5–9 years) were
reported undernourished (BMIZ < −2SD), in contrast to 33.1%
in Wardha. However, in Wardha, 54.1% and 51.8% of
adolescents (10–14 and 15–17 years) were undernourished
(BMIZ < −2SD), in contrast to 29.5% and 17.5% in
Koraput. In both locations, the percentage of women with
CED (BMI < 18.5) (47%) was found to be higher than for
men (39%). Table 2 gives the anthropometric and biochemical
parameters of the study population.
The biochemical analysis indicated that, in both locations,
about 33% of children under age five had VAD. About 65% of
children under age five in Koraput and 73% in Wardha had
anaemia. In Wardha, the majority (71.4% and 73.3%) of girls
in the age groups of 12–14 and 15–17 years respectively
reported anaemia while it was 58.8% and 64.4% for these age
groups in Koraput. The percentage of non-pregnant
non-lactating women with anaemia was 78.4% in Wardha, and a little
lower at 64.8% in Koraput. In both Wardha and Koraput, 55–
60% of pregnant women and 67–71% of lactating women
were reported anaemic.
3.3 Food consumption pattern and dietary diversity
Tables 3 and 4 give the average per day consumption of
different foods and the percentage of households consuming
<70% RDI of different food groups. The average intake of
cereals and millets ranged from a low 323.1 g in Wardha to
a high 563.9 g in Koraput. The consumption of rice was
observed high in Koraput (509.6 g) with limited finger millet
(77.3 g). In Wardha, the consumption of wheat (233.3 g)
was high, followed by rice (113.1 g). Consumption of cereals
and millets was at >70% of RDI by 78.5% of households in
Wardha and 96.6% in Koraput. The average consumption of
pulses was 61.1 g in Wardha, but only 34.7 g in Koraput. The
percentage of households consuming pulse-protein <70% of
RDI ranged from as high as 75.4% in Koraput to 40.5% in
The average daily consumption of green leafy vegetables
and fruits in Wardha and Koraput was well below the
suggested level of 100 g. Consumption of green leafy vegetables
by more than 90% of households was <70% of RDI. The
Table 4 Distribution (%) of households according to level of food
intake at RDI* (<70%) in two villages in India
Cereals and millets
Pulses and legumes
Green leafy vegetables
Roots and tubers
Fats and edible oils
* RDI Recommended Dietary Intake
average consumption of root and tubers and other vegetables
in Wardha and Koraput was well below the recommended
level of 200 g per capita per day. Consumption of roots and
tubers and other vegetables by more than 95% households in
Wardha was at <70% of RDI in contrast to 76.3% and 77.4%
respectively in Koraput.
The average consumption of fish or other sea foods in
Wardha and Koraput was 2.2 g and 11.0 g respectively. A
similar intake pattern was observed for animal products. The
average intake of milk and milk products in both the study
areas was well below the RDI levels, with more than 99% of
households consuming <70% of RDI.
In Wardha, compared with RDI levels, the average
consumption of sugar-related products was higher whilst that of
fats and edible oils was comparable. The proportion of
households with an intake of sugar-related products and fats and
edible oils at <70% of RDI was only 6.2% and 37%
respectively. In contrast, in Koraput, the average consumption of
sugar-related products and fats and edible oils was below the
RDI levels with 65.7% and 85.7% of households consuming
<70% of the RDI of these products.
For food source, 76% of the households in Wardha
reportedly sourced wheat and rice from the market and the
remaining 24% from the public distribution system (PDS).3 In
Koraput, about 43% of households consumed home-grown
rice, 43% sourced it from the PDS and the remaining 14%
from the market. The source for finger millet was reported
as mainly market (70%) and the remaining was home-grown
(30%). In both the study areas, most households reported the
market as a major source of benefitting non-cereal foods.
3.4 Relating socio-demographic variables and nutritional
Associations between demographic and socio-economic
variables with individual anthropometric measurements revealed
a statistically significant relationship with the dwelling and
toilet types in both Wardha (χ2 = 14.42, P < 0.05;
χ2 = 6.28, P < 0.05) and Koraput (χ2 = 13.88, P < 0.05;
χ2 = 18.51, P < 0.05). In addition, in Wardha, cooking fuel
(χ2 = 7.69, P < 0.05) and in Koraput, monthly expenses on
food (χ2 = 12.48, P < 0.05), education of household heads
(χ2 = 14.61, P < 0.05) and landholding size (χ2 = 19.23,
P < 0.05) were found to have statistically significant
associations with individual anthropometric measurements.
Tables 5 and 6 show the relationship between
sociodemographic variables and anthropometric measurements,
based on student’s t-test. In Wardha, the practice of open
defecation had a significantly higher risk of underweight and
3 PDS is a social protection measure of the Government of India to make
available mainly staple food grains (rice and wheat), and sugar at a subsidised
price to socio-economically weak households.
Relationship between socio-demographic variables and anthropometric measurements of children under age five in two villages in India
wasting among children below five years of age and CED in
adults. Wood-fire cooking had a significantly higher risk of
underweight and stunting among children below five years
and CED in adults. The kutcha house type had significantly
higher risk of reduced BMI in school-age children,
adolescents and adults. In Koraput, household heads with no formal
Table 6 Relationship between socio-demographic variables and
anthropometric measurements of school-age children and adolescents (6
to 17 years) and adults (> = 18 years)
BMI < 18.5
Open defecation −1.99 1.11 0.91
Toilets −1.98 1.16
Types of cooking fuel
Firewood −1.98 1.12 0.57
Gas −2.19 0.96
Semi-pucca −1.90 1.09 0.04*
Kutcha −2.10 1.15
Amount of money spent on food monthly (Rs.)
< 1000 −1.59 0.97 0.03*
> =3000 −1.38 0.95
Household heads education
No education −1.51 1.06 0.19
Primary −1.61 1.05
Secondary −1.57 1.04 0.66
Semi-pucca −1.53 0.98 0.78
Kutcha −1.55 1.12
Significance at *P < 0.05
education had a higher risk of household members being
undernourished. Similarly, the lesser the amount of household
expenditure on food showed a significantly higher risk of
reduced BMI in school-age children, adolescents and adults.
Examining the association of demographic and
socioeconomic variables with biochemical measurements revealed a
statistically significant relationship with monthly expenses on
food (χ2 = 11.36, P < 0.05) and education level of head of
household (χ2 = 28.08, P < 0.05) in Wardha. In Koraput, the
dwelling type (χ2 = 6.80, P < 0.05), source of drinking water
(χ2 = 13.25, P < 0.05) and occupation of household head
(χ2 = 21.23, P < 0.05) were found to have statistically significant
associations with biochemical measurements of children under
age five and adolescent girls and women aged 12 to 45 years.
Table 7 shows the association between socio-demographic
variables and anaemia, based on student’s t-test. In Wardha,
mean haemoglobin levels were found to be significantly lower
(or higher prevalence of anaemia) for children in households
spending less than Rs. 3000 per month on food. Heads of
households having no formal education had statistically
significantly lower mean haemoglobin levels for children under
age five and adolescent girls and women aged 12 to 45 years.
In Koraput, children under age five, adolescent girls and
women aged 12 to 45 years in kutcha-type households,
sourcing drinking water from a tube-well and also
occupation of the household head in wage and salary
labour were found to have statistically significantly lower
mean haemoglobin levels. In both study areas, mean
haemoglobin levels were found to be less than the
3.5 Relating nutrition status and DDS
In both the study areas, a statistically significant association
was found to exist only between DDS and BMI of adults
(>18 years) as seen from Table 8, indicating that mean BMI
significantly (P < 0.05) decreased as the DDS decreased
from high to medium to low in Wardha and from high
to low in Koraput. Only in Koraput, a statistically
significant relationship (P < 0.05) was found between DDS
and haemoglobin levels of adolescent girls and women
aged 12 to 45 years, implying significantly lower
haemoglobin levels (higher prevalence rate of anaemia)
in this category, as the DDS decreased from high to
In 2012, both Koraput and Wardha figured in the coverage list
of the multi-stakeholder nutrition programme for districts with
a high burden of malnutrition announced by the Ministry of
Women and Child Development, Government of India.
Nutritional status of children under age five is a key indicator
for the assessment of household food security. Taking into
account different indicators of under-nutrition, the more than 40%
underweight (low weight for age), 35% stunting (low height for
age) and about 27% wasting (low weight for height) we found
among children under age five in the study areas appears
unacceptably high. Similar observations of high rates of child
undernutrition among the rural population in India were reported by
Sathyanath and Rashmi (2013)
Gragnolati et al. (2005)
Childhood under-nutrition directly affects the development of
children by retarding physical and mental development, increases
susceptibility to infections, and diminishes intellectual ability and
(Caulfield et al. 2006)
. The prevalence rate of
under-nutrition in school-age children (5–9 years) was found to
be higher in Koraput than in Wardha; the proportion of
undernourished adolescents (10–14 and 15–17 years) was higher in
Wardha. The overall nutritional status of adult men and women
in the survey area also indicated a serious problem: 39% of the
men and 47% women suffered from CED, with the proportion
higher among women. This observation supports
del Ninno et al.
) that women in many poor economies are more
caloriedeficient and often suffer from CED, as compared to men.
Our study indicates a higher prevalence rate of anaemia in
children under five years of age, girls (12–17 years), women
(18–45 years) and pregnant women. Iron-deficiency anaemia,
especially during pregnancy, is reportedly associated with
maternal mortality, preterm labour, low birth-weight, and infant
(Zimmermann and Hurrell 2007)
irondeficiency affects child cognitive and motor development and
is a serious contributor to childhood morbidity
. As high as 33% of children overall were found
with VAD. VAD is generally associated with decreased
dietary intake of preformed vitamin A and its precursors, together
with a high prevalence of infectious diseases
Relationship between nutrition status and dietary diversity score (DDS) in two villages in India
BMI > =18 years
BMI > =18 years
Haemoglobin level (12 to 45 years girls & women)
Significance at *P < 0.05
Low dietary diversity
Medium dietary diversity
High dietary diversity
general, evidence of high incidence of under-nutrition and
micronutrient deficiency among the rural population in both
Wardha and Koraput is of concern, thus reiterating the need
for multi-sectoral nutrition interventions.
4.1 Socio-demographic and nutritional status
Previous studies have reported that socio-economic and
sociodemographic variables have substantial influence on
(Sen and Mondal 2012; Frongillo et al. 1997)
the present study, the socio-economic backwardness of the
surveyed indigenous populations was visually evident in their
dwelling conditions. Overall, kutcha houses made up of straw
roof and mud walls were the most common types. Access to
clean and safe drinking water contributes to improved
nutrition status (Leipziger et al. 2003). UNICEF/WHO (2015)
considers protected water supplies from piped/tap water and
tubewells as safe for drinking, while the other unimproved sources
are considered as unsafe. Going by this classification, only
52% of households in Wardha and 66% in Koraput have
access to safe drinking water. Further, most households in
Koraput do not have information about whether
tube-wellsourced drinking water is free from arsenic. Lack of improved
environmental sanitation and hygiene is the main cause of
excreta-related diseases such as diarrhoea and cholera, and
(UNICEF/WHO 2015; Spears 2013)
Most households in the study areas were found to practice
open defecation. Indoor air-pollution due to use of solid fuels
is the second most critical environmental risk factor after poor
water and sanitation, contributing to numerous respiratory
diseases (Bruce et al. 2006). Among surveyed households, wood
fire was the most popular source of domestic energy used for
cooking. This was largely due to its availability and
inexpensive nature, and also lack of access to contemporary cooking
fuels. Looking at these socio-demographic variables, no single
factor with a high influence for under-nutrition could be
isolated. In general, substandard living conditions of the
surveyed households reflected a higher risk of household
members to under-nutrition and micronutrient deficiency.
Most household members were of working age (18 to
44 years), indicating the potential for labour-intensive
agriculture. The majority of households were nuclear or extended
nuclear families signifying increased disintegration of the
traditional joint family. Two major factors contributing to an increase in
nuclear families included resource scarcity (e.g. food, income)
and a problem of lack of space for accommodation. Levels of
education determine the ability of a household to access income
and have positive impacts on various aspects of health and
. Looking at the surveyed household heads,
most either had no education or were educated only to the
primary level. This was consistent even for other household
members in the study areas. The heads of households with no formal
education in Koraput and some primary level of education in
Wardha showed significantly higher risks of under-nutrition and
micronutrient deficiency among household members.
et al. (1997)
also reported that illiterate household heads showed
significantly higher risks of under-nutrition, particularly wasting
among children in their households.
Other determinants of under-nutrition were the occupation of
household heads and amount of money spent on food.
Occupation of household heads as casual labourers or daily wage
earners (viewed as a low productive activity as it provides
workers with just a basic income for survival) showed
significantly higher risk of under-nutrition and micronutrient
deficiency. In addition, they reportedly migrate temporarily to nearby
areas especially during the Rabi (dry) season for employment
opportunities to diversify income. According to
, the amount of money spent on food has a direct
relationship with the nutritional status of household members. In
both study areas, the lesser the amount of money spent on food
indicated less access to food, and thus significantly higher risk of
under-nutrition and micronutrient deficiency. Overall, in both
study locations, socio-economic and socio-demographic
variables indicated the lack of basic social infrastructure and low
human development with very poor welfare indices.
4.2 Agriculture, nutrition, and their disconnect
The two main agricultural seasons in the areas are the Kharif
and Rabi. Kharif cropping is conducted from June to October
correlating with the southwest monsoon (June to September)
and hence assured rainfall. Each year more than 80% of total
rainfall is received from the southwest monsoon
. However, uncertainty in the distribution of monthly
rainfall patterns (above- or below-normal rains) results in
positive or negative effects on cropping and yield performance.
Rabi cropping is from November to March, involving cool
and dry season crops. These crops are usually grown using
residual soil moisture after the southwest monsoon, and with
supplementary irrigation. More often than not, low soil
moisture affects the sowing of seeds. Terminal drought is a major
production constraint, as crops are highly sensitive during
later growth stages. In both of the study areas, rain-fed
agriculture (Kharif) is widely practiced. Although
farmhouseholds cultivated in the Rabi, the area planted was very
limited, because of a lack of water and irrigation facilities.
Variable amounts of crop-saving irrigation is always required
to avoid crop failures in the Rabi season. Captive water (e.g.
tube well) is the only form available for irrigation in the study
locations. Thus the livelihood and economy of farmers is
highly influenced by spatio-temporal variability of rainfall.
Typically, farmers depended only on local varieties of
crops based on their Kharif season characteristics. If the onset
of rain was early or normal, then local late maturing varieties
were preferred. If rains started late, early maturing varieties
were preferred to maintain potential yield. The surveyed
farmhouseholds had experienced and managed complex and
heterogeneous environments to cultivate rain-fed crops using
their indigenous knowledge in the past. But recent reported
abrupt changes to the local climate
(Birthal et al. 2014)
indicated by fluctuating air temperatures and precipitation, has
substantially affected local weather and impacted Kharif crop
production. In addition, under marginal growing conditions,
local crop varieties have resulted in a loss of competitiveness
and lower productivity levels. Limitations identified in our
survey, as also reported in many rural agricultural settings
(e.g. Bergamini et al. 2013; Altieri et al. 2015; Snapp et al.
, such as the neglect of several naturally-fortified and
drought-tolerant food crops, the use of old types of seed and
outdated agronomic practices, a focus on repetitive cropping
patterns, insufficient crop diversification and declining soil
fertility pose greater challenges for successful crop yields with
variable weather conditions. Similar to the observations of
, most of our surveyed farm-householders
perceived climate risk scenarios to be a natural process, rather
than a consequence of human activity. Overall, the lack of
technology and knowledge transfer in conjunction with
inadequate adjustments to crop management and inappropriate
farm-level resilience and adaptation strategies to
environmental perturbations are the main reasons for the inadequate
farming situation, worsening food and nutrition security in our
study villages; these also posed a serious risk of undermining
the livelihoods of farm households.
Farm-households in Koraput and Wardha varied
substantially in their landholding size and the choice of farming practices.
In Koraput, the existing cropping pattern reflected a
predominance of subsistence cropping. The soils of Koraput are red
loamy and red sandy soils, ideal for rice cultivation
Agriculture Policy 2013)
. The principal crop in the Kharif
season was rice with very limited millets, and in the Rabi season,
groundnut, green gram, maize, finger millet and black gram
were grown, occupying very limited areas. Finger millet has
been reportedly reliable and resilient to weather aberrations.
Most were marginal farmers with farm landholdings less than
one ha, often less than an acre (1 acre is equivalent to 0.40 ha or
4047 m2). The small land areas owned by farm-households
appeared highly uneven, sloped and undulated, and were often
fragmented into lowland, medium land and upland across the
village. We observed that the restricted and asymmetric farm
size resulted in a shortage of farmland for some crop husbandry
practices, limiting production and also the economic potential.
Although households depended more on home-grown foods
than from markets, other challenges
(also reported in State
Agriculture Policy 2013)
included geographical remoteness,
absence of adequate credit, and a shortage of technological inputs
coupled with marketing risk when growing other crops. Many
of these factors contribute to the existing conservative
approaches to cropping. In view of the very limited landholdings
by most marginal farmers, a lack of access to off-farm income
was the reason reported by farmers for not being able to
overcome food shortages or to access non-cereal foods, as evidenced
from the household food intake patterns we found.
Unlike Koraput, Wardha was dominated by small and
semi-medium farmers, but the percentage of landless persons
appeared very high. The landless population depends on
multiple inconsistent sources to sustain their livelihood and hence
are more prone to recurrent food shortages. The soil of
Wardha is characterised by black clayey or loamy soils and
stony shallow black soils that are highly suitable for
cultivation of cotton. The principal crops in the Kharif season were
Bt-cotton + pigeon pea, with limited soybean and sorghum. In
the Rabi season, household food security crops like sole
wheat, wheat + chick pea and sole chick pea occupying very
limited areas were grown. The existing cropping pattern
indicated mostly high input- and high output-based commercial or
cash cropping. The potential for high value crops and easy
market access for their produce heavily contributed to the
observed pattern of cultivating cash crops
(Gavali et al.
. Most of the wheat and rice consumed by households
came from the market and the PDS. This has extensively
limited the area of production and consumption of
naturallyfortified millets and sorghum, which were the preferred staple
foods until about two decades ago
(Gali and Parthasarathy
. Additionally, dependence on supplies of food
grains from elsewhere and markets cause households to be
more vulnerable to food insecurity
(Huang et al. 2017)
especially when there is a fall in income during times of hardship
(e.g. crop failures due to biotic or abiotic stressors or crop
damage by wild animals). The observed deficit in household
consumption of calories and other non-cereals is evidence of
inconsistent household income per capita.
Overall, most surveyed households owned farm animals (a
type of capital asset) and practiced combined crop-livestock
farming. Among farm animals, cows were important as they
produce milk of high nutritional value. In addition, livestock
directly support agriculture through manure and draught power;
whereas small animals, particularly poultry, generate income
from eggs and meat. Most households reported that animal food
products were not a significant part of their diet. Hence,
household consumption of meat and poultry, and milk and milk
products was found to be well below the RDI levels, indicating
negligible animal-sourced food in the diets. Though farm animals are
viewed mostly as a source of income, cash from animal sales was
often not used for shifting household diet habits to include other
food groups such as multi-nutrition-rich fruits and vegetables as
observed by household food consumption patterns. Our surveyed
farm-households reported that the cash generated was used for
either medical emergencies or other planned expenditures (e.g.,
marriage), as common in resource-poor communities.
Nevertheless, no access to animal health services for ruminant
livestock and a higher incidence of Ranikhet disease in poultry
were identified as reasons for lower economic returns.
Previous studies have shown that an effectively designed
homestead garden contributes to improved household diet and
nutrition and is also an added source of income
(Masset et al.
. Considering fruits and vegetables are often expensive to
buy in markets, potentially restricting rural households’
affordability, homestead gardens are viewed as a viable option for the
enrichment of diets
(Galhena et al. 2013)
. In both Wardha and
Koraput, traditional gardening was practiced adjacent to the
household settlement. Household food preferences and local
availability of input materials largely determined the type and
mix of fruit and vegetable crops grown. Based on water
availability, gardening was practiced either throughout the year or
limited only to the Kharif season. Challenging factors reported
in our survey such as seed availability, water shortage, poor
management and inadequate technological inputs hindered
garden production and productivity levels to a large extent.
Identified production constraints were evidenced when
examining household food intake, with consumption of fruits by more
than 94% of the households in both Wardha and Koraput being
less than 70% of RDI levels. Similarly, consumption of root and
other vegetables by more than 95% households in Wardha and
76% in Koraput was less than 70% of RDI. Most surveyed
households despite having backyard space did not practice
homestead gardening due to limited resource availability and
lack of institutional support.
Both the study areas have a monotonous dietary pattern with
just one or two major food groups, 24-h recall data were used to
measure dietary diversity as it seems more reliable and precise
(Oshaug 1997; Chavaz and Huenemann 1984)
, and low dietary
diversity is often reported the key cause of under-nutrition and
(Ruel 2002; Shetty 2009)
. This is also
evidenced from our study findings where DDS indicating low,
homogeneous and poor dietary diversity contributed to
increasing anaemia rates in adolescent girls and women in Koraput, and
CED in adults (>18 years) in both Koraput and Wardha.
Generally, other mediating factors (e.g. hygiene and sanitation)
being favourable, dietary diversity improves the
nutritionabsorption rate of the individuals and thus may have beneficial
(WHO & FAO 2003)
In Koraput, despite a higher intake of calories than the RDI
levels, a higher prevalence of under-nutrition was observed,
implying that calorie expenditure exceeds calorie intake. That
negative energy balance causing under-nutrition might be due
to the significant high amounts of energy spent in farming and
other household activities, as compared to the energy intake,
besides very limited intake of other non-cereal foods.
Woo et al.
also reported that energy expenditure increased by
increasing the time spent in physical activity, as compared to
calorie intake. In Wardha, although iron intake was comparable
with RDI levels, a higher prevalence of iron-deficiency
anaemia was witnessed, indicating lower absorption rates of iron.
With wheat being a staple food, iron absorption may be
potentially inhibited by phytates, as reported by
Garcia-Casal et al.
. A similar situation was also reported in the rural
population in Iran, where high iron-deficiency anaemia was found
despite the diet including high iron intake with wheat as a staple
(Haghshenass et al. 1972)
. Other reasons for a high
prevalence of under-nutrition and micronutrient deficiency in both
of our study areas were mostly due to diets with few animal
products, fruits and vegetables.
Grillenberger et al. (2006)
reported that household diets containing few animal products,
fruits and vegetables and predominantly consisting of cereals
and legumes is associated with not only low intakes of several
vitamins and minerals and poor mineral bio-availability, but
also simultaneous deficiencies of multiple nutrients.
Variation observed in choice of farming orientation
(commercial or subsistence), possession of animal components and
practice of traditional homestead gardening between Wardha and
Koraput, however, did not reflect major differences in the mean
DDS and under-nutrition or even micronutrient deficiency status.
Although DDS indicated seven food groups as a part of the
individual diet, household food consumption patterns showed
that the proportion of food intake from each food group was well
below the RDI levels. As reported by Global Panel (2015) and
also evident from the present findings, when farm-households
move from subsistence-based to mostly cash-based commercial
cropping, dietary patterns do not necessarily shift in the desired
direction of high dietary quality and diversity. High intake of
sugar and fat observed in commercial-crop-dominated Wardha
rather than a more diversified food basket substituting often
consumed staples, is indicative of spending of income from the sale
of commercial crops. Furthermore, some food commodities,
especially fruits and vegetables purchased post farm gate, are
reportedly costlier than those produced within the farm. The overall
scenario indicates a major disconnect of agriculture-nutrition
linkages. Food and diets lacking diversity and without
nutrition-focused farming systems including boosting income
through commercial cropping (solely indirect effects) or
monotonous diet by subsistence farming (solely direct effects) may not
be appropriate to improve household nutrition and health status.
A combination of innovative and integrated agriculture-nutrition
strategies that can potentially diversify diet (directly) and better
use of income generated for nutrition adequacy (indirectly),
concurrently with other interventions to improve education, health,
sanitation and household infrastructure stand a better chance of
combating the under-nutrition and micronutrient deficiency
(Das et al. 2014)
. We present some of these opportunities as
ways forward in the remaining section.
5 Conclusion and way forward
Overall, the nutritional status, dietary diversity and cropping
patterns in both Wardha and Koraput reflected the influence
of local socio-economic and environmental aspects,
farmhousehold decision making and the choice and opportunities
of farming approaches. Our survey findings indicated several
areas for action to improve household food and nutrition
security. Establishing FSN (nutrition-sensitive agriculture) to
improve household dietary diversity and income was the central
objective of the present study. From the identified disconnect
between agriculture and human nutrition, the FSN study
identified potential routes to effectively overcome food and
nutrition insecurities such as changes in crops (use of more naturally
or bio-fortified crops); improvement of farming practices (that
can enhance productivity, diversify crops and conserve soils);
interconnection with animal components, including the
conduct of animal health camps (for de-worming and vaccination)
emphasizing disease preventive strategies; greater access to
technologies and inputs through institutional and market
linkages; promotion of homestead gardening (including rain water
harvesting); and sustainable farm business models (processing
and storage), especially for the landless.
Women are central to rural economies as witnessed by their
co-participation in household decision making and in farm
activities. Women are frequently recognised as catalytic agents
against hunger and their sensitisation with nutrition education
and training to increase women - centred backyard gardening or
animal components will straightaway improve household diets
and nutrition outcomes with additional access to income.
Water is crucial in these food vulnerable areas. Improving
access to water, linked with improved agronomy including
seed, fertilizers and technology will stabilise crop production.
Agricultural water management is important to reduce
poverty, optimise yield and income stability with additional benefits
in improvement of nutritional status, health and societal equity
(Valipour 2015; Yannopoulos et al. 2015)
. To increase the
number of ‘green’ days and cropping intensity and to
encourage more households to practice Rabi cropping, MSSRF is
leveraging extant government schemes, such as lift and drip
Fig. 3 Establishing structure of
the Farming System for Nutrition
irrigation and watershed development. Identified areas in our
survey that need increased attention include watershed
management, de-silting and deepening of water bodies to recharge
underground water resources, digging ‘Jalkund’ (rainwater
collection and storage through ponds/pits) and
microirrigation using drip/sprinkler systems. Other considerations
may include non-conventional water resources such as treated
wastewater to supplement irrigated agriculture, as the volume
of non-treated discharged wastewater in India is reportedly
very high (Valipour and Singh 2016). Such efforts will
potentially enhance the livelihoods and nutrition of small and
marginal farmers in the future.
To effectively operationalise the FSN approach (see Fig. 3),
farm-households need to be engaged in planning, and jointly
work with other stakeholders to identify key FSN
interventions. FSN has to be tailored to the local socio-economic
situation, cropping systems and weather risks, farm-household
requirements, institutional support and policy and programme
environment. To ensure sustainable and long-term adoption
and outcomes of FSN, households need to witness interim
benefits from each intervention activity in terms of improved
food and nutrition security and increasing productivity. Our
attention in planning is on production-consumption-nutrition
links to ensure healthy diets through food diversity. This will
potentially address major nutritional problems experienced by
the surveyed households. Our field-level investigators will
monitor and measure the experiences of each implemented
FSN intervention with oversight from experts, and the
understanding that changes to nutritional status will be the very last
to be affected, in the process, identifying barriers and
motivation for early adapters or innovators. Comparison with the
present baseline survey findings for each activity will provide
necessary evidence for supporting multi-level policy
dial o g u e s . I n a d d i t i o n t o p r o p o s e d F S N s t r a t e g i e s ,
Identify existing disconnect between agriculture-nutrition linkages
through baseline survey
Engage in planning with farm-households and stakeholders to
identify FSN interventions in various settings
Piloting FSN interventions in selected farm-households, who are
able to follow a set of guidelines
Performance evaluation - crop productivity/nutritional outcomes,
and measuring farm-households experiences and concurrent
Identify location-specific potential FSN interventions that
strengthen agriculture nutrition links for resource poor
simultaneously mediating with existing government
programmes related to the non-agricultural interface (e.g.
Swachh Bharat Abhiyan, a campaign of the Government of
India to improve communal cleanliness and sanitation and
eliminate open defecation) will provide overall greater proof
of impact. Specific approaches under commercial versus
subsistence farming setups prevalent in Wardha and Koraput, will
also provide interesting and meaningful lessons.
This study is one of the first to assess the feasibility of
agriculture-nutrition linkages in districts in India with a high
prevalence of severe under-nutrition. Although, we were
fortunate to build on the core resources of MSSRF already
operating in both Wardha and Koraput, substantial time will be
required in establishing the process, demonstrating FSN
interventions, performance evaluation, and finally scaling up for
broader application of these types of initiatives. An end line
survey of key FSN interventions in selected farm-households
will measure experiences with respect to nutrition (health,
dietary diversity) and non-nutritional dimensions (income,
production diversity). The outcomes will provide and offer
greater practical evidence and proof to policy makers for
integrating and leveraging agriculture and nutrition to alleviate
under-nutrition and poverty in rural India.
Acknowledgements This research was conducted as part of the
Leveraging Agriculture for Nutrition in South Asia (LANSA) research
programme consortium, funded by UK Aid from the UK Government.
The views expressed do not necessarily reflect the official policies of the
Government of the UK. The authors gratefully acknowledge the
contribution of Mr. Akshaya Panda and Mr. Mahesh Maske, Coordinators of
the FSN study, and Ms. Jasaswani Padhy and Ms. Rupal Wagh, Research
Associates (Nutrition) at Koraput and Wardha respectively, who oversaw
the conduct of the baseline survey and data entry at the two locations and
the field teams who collected and entered the data. The authors also thank
Mr. Rohit Parasar for insightful comments and suggestions. Special
thanks to Dr. Prakash Shetty, CEO-LANSA for expert feedback in
revising the manuscript.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
The study was approved by the Ethics Committee of the MSSRF
Board of Trustees. In addition, informed consent was obtained from
district level officers in Wardha and Koraput. Ethical clearance oral consent
was obtained from the head of household before collecting household
information and from all subjects selected for anthropometric and
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Nithya D J is working as a
Nutrition Scientist in LANSA at
MSSRF, Chennai, India. She
holds a doctorate degree in Food
Science and Nutrition from Tamil
Nadu Agricultural University.
She has experience working in
various projects on food
processing technology and has conducted
training on food processing and
v a l u e a d d i t i on f o r f a r m e r s ,
women’s self help groups and
entrepreneurs. In her current role,
she is responsible for overseeing
the conduct of nutrition status
assessment surveys in villages under the Farming System for Nutrition
study, including the analysis and interpretation of data and coordination
of the nutrition awareness component of the study.
Raju S is working as a Senior
Research Fellow under LANSA
at MSSRF. He holds a Masters
i n E c o n o m i c s f r o m
B h a r a d h i d a s a n U n i v e r s i t y,
Trichy, Tamil Nadu, India, and
has six years of experience
working in various projects with the
Madras School of Economics,
Chennai. Raju has expertise in
sampling design, framing survey
tools, questionnaire templates,
pilot testing, conducting and
coordinating household and market
surveys and focus group discussions,
data management, analysis and reporting. He is also experienced in
statistical analysis using packages like STATA and SPSS. In addition to
his responsibility of overseeing the collection and managing survey data,
he is engaged in studying the feasibility and challenges of introducing
millets in the Public Distribution System in India.
Bhavani R V has been working
on food and livelihood security
issues at MSSRF for more than
fifteen years. Holding a PhD in
Economics from the University
of Madras and an erstwhile
banker, she is currently Programme
Manager, LANSA, responsible
for coordinating with partners in
the consortium research
programme as well as oversight of
r e s e a r c h u n d e r L A N S A a t
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Vijaya Bhaskar A V worked as an Agronomist on the Leveraging Agriculture for Nutrition in South Asia (LANSA) research prog r a m m e a t t h e M . S . S w a m i n a t h a n R e s e a r c h Foundation (MSSRF) for a brief period in 2016. He holds a PhD in Agricultural Systems funded by the John Oldacre Foundation from Coventry University, UK and an MBA from the Royal Agricultural University , UK. Vijay is currently a Postdoctoral Researcher in the Department of