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IMPACT PATHWAYS FROM AGRICULTURAL POLICY TO IMPROVED

NUTRITION OUTCOMES: The Case of the PROMISE Project in Northeastern Ghana

Joseph Abazaami

Institute for Interdisciplinary Research and Consultancy Services

University for Development Studies

Post Office Box TL 1350, Tamale, Northern Region

Evans A. Atuik

Institute for Interdisciplinary Research and Consultancy Services

University for Development Studies

Post Office Box TL 1350, Tamale, Northern Region

Viola N. Dasoberi

Millar Institute for Transdisciplinary and Development Studies (MITDS)

Millar Open University

Post Office Box 607, Bolgatanga, Upper East Region

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Abstract

Investment in agriculture is widely seen as “a critically important opportunity for reducing

malnutrition.” (Herforth et al. 2012). There have been repeated calls for the international

community to place a higher priority on “unleashing” (IFPRI 2012), “leveraging” (Pell at al.

2011), “reshaping” (Fan and Pandya-Lorch 2012), or “realizing” (IFAD 2011) the opportunities

offered by agriculture to enhance nutrition and health. One of the stated aims of the renewed

focus on agriculture is to encourage agricultural policies and programmes to become “nutrition-

sensitive” (BMGF 2012; USAID 2011), or more specifically, to make “agriculture work for

nutrition” (FAO 2012). In 2016, the world embarked on implementing the 2030 Agenda for

Sustainable Development, with the goal of eliminating extreme poverty and hunger. The UN also

endorsed the Framework for Action that emerged from the Second International Conference on

Nutrition that culminated in the launch of the UN Decade of Action on Nutrition (2016–2025).

The G7’s commitment to prioritizing nutrition and the G20’s emphasis on agricultural innovation

for sustainable development are sterling milestones that underscore the importance of improved

policy targeted at making agriculture work for nutrition. The big question worth academic

thought and reflection is, how? Against a backdrop of demands for greater accountability, many

donors and national governments are calling for evidence-based programming (Mallet et al.

2012). This has precipitated renewed interest in rigorous empirical information that can inform

policymakers on what kinds of agriculture to invest in (through research or programming) that

will have positive benefits for nutrition outcomes and livelihood security, particularly among

mothers and children. So far, that search has come up short. This paper seeks to contribute to

ongoing work at many institutions aimed at identifying priority knowledge gaps, determining the

best research approaches needed to fill those gaps, and exploring how to better support

agricultural policy and programme implementation with sound empirical evidence of ‘what

works’ for improved nutrition outcomes under which circumstances and why. The study

attempted to do this by specifically examining CARE International’s Linking Initiatives,

Stakeholders and Knowledge to Achieve Gender-Sensitive Livelihood Security (LINKAGES)

programme (PROMISE Ghana). Analysis was focused on the Women’s Empowerment in

Agriculture Index (WEAI) and the Logical framework for assessing impact of agricultural

interventions on nutrition (as proposed by Masset et al. 2011). Key findings of the paper include

evidence of improved nutrition, strengthened and diversified livelihoods (through skill

acquisition for processing and marketing soya and cowpea products), and shifts in gender

dynamics that foster and promote women’s agency in supporting improved nutrition outcomes.

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1.0 Introduction

Investment in agriculture is widely seen as “a critically important opportunity for reducing

malnutrition.” (Herforth et al., 2012). There have been repeated calls for the international

community to place a higher priority on “unleashing” (IFPRI, 2012), “leveraging” (Pell at al.,

2011), “reshaping” (Fan and Pandya-Lorch, 2012), or “realizing” (IFAD, 2011) the opportunities

offered by agriculture to enhance nutrition and health. The donor community has been pretty

much responsive, bringing a larger budget share to bear on the agriculture sector since the mid-

2000s, reversing the steep decline of the previous decade (OECD 2012). One of the stated aims

of the renewed focus on agriculture is to encourage agricultural policies and programmes to

become “nutrition-sensitive” (BMGF, 2012; USAID, 2011), or more specifically, to make

“agriculture work for nutrition” (FAO, 2012). In 2016, the world embarked on implementing the

2030 Agenda for Sustainable Development, with the goal of eliminating extreme poverty and

hunger. The UN also endorsed the Framework for Action that emerged from the Second

International Conference on Nutrition that culminated in the launch of the UN Decade of Action

on Nutrition (2016–2025). The G7’s commitment to prioritizing nutrition and the G20’s

emphasis on agricultural innovation for sustainable development are sterling milestones that

underscore the importance of improved policy targeted at making agriculture work for nutrition.

The big question worth academic thought and reflection is, how?

Against a backdrop of demands for greater accountability, many donors and national

governments are calling for evidence-based programming (Mallet et al., 2012). This has

precipitated renewed interest in rigorous empirical information that can inform policymakers on

what kinds of agriculture to invest in (through research or programming) that will have positive

benefits for nutrition outcomes and livelihood security, particularly among mothers and children.

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So far, that search has come up short. According to Thompson and Amoroso (2010), there is still

“insufficient understanding of the evidence base on how best to achieve this potential.” Indeed,

an assessment of 23 studies of agriculture interventions, commissioned by DFID found “no

evidence of impact on prevalence rates of stunting, wasting and underweight among children

under five.” (Masset et al., 2011) Thus, knowledge about agriculture’s impact on nutrition can be

summarized in the words of Hawkes et al. (2012): “Despite the clear potential for agricultural

change to improve nutrition in low and middle income countries, the evidence base for this

relationship is poor. Recent systematic reviews of studies which have evaluated agricultural

interventions for improving nutrition reveal little strong evidence of impact, and a need for more

and better designed research.”

This research project is intended to contribute to ongoing work at many institutions aimed at

identifying priority knowledge gaps, determining the best research approaches needed to fill

those gaps, and exploring how to better support agricultural policy and programme

implementation with sound empirical evidence of ‘what works’ for improved nutrition outcomes

under which circumstances and why. The study attempted to do this by specifically examining

CARE International’s Linking Initiatives, Stakeholders and Knowledge to Achieve Gender-

Sensitive Livelihood Security (LINKAGES) programme (PROMISE Ghana). Analysis was

focused on the Women’s Empowerment in Agriculture Index (WEAI) and the Logical

Framework for Assessing Impact of Agricultural Interventions on Nutrition (as proposed by

Masset et al., 2011).

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1.1 Country/Problem Context and Rationale for Research Project

Ghana has been lauded as a remarkable economic success story in Sub-Saharan Africa. After a

decade of robust economic growth, and following a recent review of its national accounts, Ghana

attained middle-income status in 2011, well in advance of its 2015 Millennium Development

Goal. The country has also been successful in cutting poverty by half as well as attaining a solid

level of domestic food security by reducing malnutrition among the general population. Ghana is

an agricultural-based country, and the Government recognizes that agriculture growth has a

greater impact on poverty reduction than other sectors. The agriculture sector is the ―backbone

of the economy, representing more than 30 per cent of GDP in 2010, and employing 63 per cent

of the workforce in rural areas (IFAD, 2017). Food security conditions fluctuate from year to

year depending primarily on the nature of the growing season. Every year, families in northern

Ghana experience a hunger gap of 3 months. This gap occurs as food stocks run out months

before the new harvest is in and this season is characterized by families eating as little as one

meal a day. In 2009, information from sentinel sites indicated that 45% of granaries in Northern

Region and 40% of those in the Upper West Region were empty by June 2009.

Although not the only factor, food consumption provides the most direct link between agriculture

and nutrition, making the issue of food security at the household, community, and national levels

a major contributory factor to nutritional status. This means the low productivity in the

agriculture sector has major implications for food and nutrition security in the country.

According to the Medium-Term Agriculture Sector Implementation Plan (METASIP) 2011–

2015, the country continues to experience deficits with regard to rice, maize, sorghum, and millet

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availability, resulting in the need for food imports to make up for the cereal production shortfall.

Indeed, further analysis indicates deficits in fish and other important food commodities as well.

Moreover, each one of the specific regions constituting Northern Ghana; Upper West, Upper

East, and Northern Regions has a poverty story of its own to tell. Poverty in Upper West Region

is still the most pervasive, at 88 per cent, a level that has not changed in 20 years. Poverty in

Upper East Region, which at 70 per cent is the next highest level of poverty, actually deteriorated

in the past 20 years. And poverty in Northern Region, with the third highest level in the country

at 52 per cent, is actually at the same level Ghana was countrywide in 1990/1991. Poverty is not

the only measure of deprivation that shows stark South-North differences — social development

indicators are also consistently worse in the North than in the South (IFAD, 2017).

The contribution of poverty in the complex relationship between food security and malnutrition

cannot be overemphasized. With more than two decades of rapid economic growth and political

stability, Ghana has emerged as a leader in Sub-Saharan Africa. Yet, despite the nation’s relative

prosperity, poverty remains pervasive, primarily in the country’s three northern regions. These

regions now account for approximately 40 percent of the population living under the poverty line

and have high prevalence of food insecurity, ranging from 11 percent to 34 percent being food

insecure (GSS, 2014).

The current Government’s Coordinated Programme of Economic and Social Development

Policies (CPESDP, 2017-2024), indicates that Ghana has made considerable progress in

improving the nutritional status of children. The proportion of stunted children in the country

declined from 33% in 1993 to 19% in 2014, while the prevalence rate of underweight children

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declined from 23% to 11%. The prevalence rate of wasting also dropped from 14% to 5% in

2014. In the recent past, Ghana has not suffered from food insecurity because of improved food

production. Domestic production of selected staple food crops continues to exceed national

demand, reflecting surpluses. Despite this positive outcome, the incidence of hunger persists in

pockets of Ghana. There is unacceptably high child malnutrition and an increased incidence of

diet-related non-communicable diseases in northern Ghana. There is also a prevalence of

nutritional deficiencies, a weak Food and Nutrition Security (FNS) institutional framework and

coordination, and a weak food control system (Republic of Ghana, 2017).

To ensure food security and promote good nutrition, the interventions to be implemented under

the CPESDP include: instituting measures to prevent food losses; promoting the production and

utilization of locally grown and nutrient-rich food; strengthening early warning and emergency

preparedness systems; developing and implementing a nutrition strategy, which adopts a life-

cycle approach to reduce malnutrition at all levels; reviewing and scaling up the Regenerative

Health and Nutrition Programme (RHNP); eliminating child and adult overweight and obesity;

and promoting research and development in FNS, (Republic of Ghana, 2017). The last policy

direction represents the area this research is geared at making at making a contribution.

This contribution is certainly not out of place as the World Bank has observed over some time

now that, while enhanced agricultural productivity is an important development goal in its own

right, “merely producing more food does not ensure food security or improved nutrition.”

(Herforth et al., 2012). FAO (2012) also acknowledges that “agriculture interventions do not

always contribute to positive nutritional outcomes.” Recognition that growing more food is

necessary but usually not sufficient to achieve good nutrition and health leads directly to

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hypothesis-building around what else might be required. What else is required from the context

of this research is to obtain empirical evidence to ascertain to what extent agricultural policies

have influenced nutrition outcomes in chronically food insecure northeastern Ghana - looking

specifically at the following three pathways linking agriculture with food consumption and

human nutrition:

• Increased consumption from increased food production;

• Increased income from the sale of agricultural commodities; and

• Increased empowerment of women as agents instrumental to improved household food

security and health and nutrition outcomes

1.2 Research Project Context

The Linking Initiatives, Stakeholders and Knowledge to Achieve Gender-Sensitive Livelihood

Security (LINKAGES) programme was a 4-year (2012-2016), multi-country initiative

implemented by CARE Canada with funding from the Government of Canada through the

Department of Global Affairs Canada (GAC). PROMISE was CARE Ghana’s contribution to the

achievement of the goal of LINKAGES “Improved livelihood security and resilience for

vulnerable women, girls, men and boys in Bolivia, Ethiopia, Ghana and Mali”. PROMISE in

Ghana sought to achieve the following intermediate outcomes: Women and girls increase

consumption of processed soya and cowpea and products; vulnerable women and girls equitably

participate in and benefit from soya and cowpea value chains; and District Assembly processes

in the two Districts support women led multi-stakeholder platforms for cowpea and soya beans.

PROMISE in Ghana was implemented in 20 communities in two districts (Garu-Tempane and

East Mamprusi) in Upper East and Northern Regions respectively reaching out to 4,460 direct

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female beneficiaries. PROMISE was implemented through two local partners; Presbyterian

Agricultural Station–Garu (PAS-G) and Partners in Rural Empowerment and Development

(PARED) working in the Garu Tempane and East Mamprusi districts respectively. PROMISE

was also implemented in collaboration with the Ministry of Food and Agriculture (MoFA) and

the Savannah Agricultural Research Institute (SARI) which provided technical support to

beneficiary communities for soya beans and cowpea production and value chain development.

The Ghana Health Service (GHS) provided technical support and education on nutritional values

of soya beans and cowpeas to women in beneficiary communities. CARE Ghana also worked

with the two District Assemblies to ensure the creation of the necessary enabling environment

for women to be involved in decision-making on issues affecting their access to resources to

improve their livelihoods. The soya bean and cowpea value chains were used as the platform to

initiate this process.

1.3 Research Objectives

The general objective of this research was to assess PROMISE project to determine if nutrition

outcomes were achieved and whether there was a good-fit between these achievements and

national nutrition and agricultural policies. Specifically, the research sought the following:

1. To investigate the extent to which the PROMISE project contributed to increased

consumption from increased food production of soya and cowpea (production-for-own-

consumption) for improved nutrition;

2. To determine if the project was successful in increasing income from the sale of

agricultural commodities (production-for-income) and how this translated to improved

nutrition in the household;

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3. To analyze the extent to which empowerment of women agriculturists has taken place

through the efforts of the project; and

4. Finally, to proffer recommendations on agriculture and nutrition policies for improved

household level consumption of soya and cowpea, individual food and nutrient intake and

nutrition status.

2.0 Conceptualizing Causal Pathways from Agriculture to Nutrition Outcomes

Most of the recent reviewers of the evidence of impacts of agriculture on nutrition have

organized literature searches and analyses around theorized causal pathways that build on the

understanding that ‘food alone is not enough’. The genesis of such thinking was the UNICEF

framework that conceptualizes immediate versus distal determinants of nutrition. That

framework places ‘inadequate dietary intake’ and ‘disease’ as two immediate drivers of

undernutrition, although the ways in which diet and disease interact are left at a high level of

abstraction. The same is true of FAO’s framework, which identifies food consumption and

utilization as direct contributors to nutrition outcomes. Both the FAO and UNICEF frameworks

suggest that focusing on dietary adequacy in the context of improved health is needed to achieve

enhanced nutrition (Webb, 2013).

However, understanding of what ‘adequate’ means has changed over time. For example,

attention of researchers during the 1990s was largely directed towards enhancing the productivity

of crops grown by smallholders who were assumed to benefit nutritionally from consuming more

of those same crops. One reported success of the mid-1990s was that, “higher calorie intake has

improved nutrition and health.” (CGIAR, 1996). By the late 1990s, much agricultural research

had shifted from the assumption that more calories meant better nutrition, toward tackling

specific nutrient deficiencies. That was an era when biotechnology was gaining more attention as

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a potentially important tool “in the struggle to reduce…malnutrition” (CGIAR 1999). Specific

crops, such as orange flesh sweet potatoes and quality protein maize (QPM), were targeted as

vehicles for delivering defined nutrients (such as betacarotene or protein with an improved

amino acid profile) into local food systems. The concept of biofortification also took off, based

on the premise that higher levels of micronutrients in target crops would meet the needs of

people deficient in those nutrients. Orange Sweet Flesh Potato and QPM have both been shown

to be efficacious and have had success in roll out in certain geographies (Low et al., 2007;

Gunaratna, 2010).

However, the establishment of the CGIAR Science Council in the early 2000s ushered in a less

nutrient-centric focus. Seeking to understand “how agriculture affects human health [and]

nutrition”, the Science Council proposed a research agenda consisting of 20 priorities selected

according to criteria that included “a refocusing on nutrition outcomes as opposed to nutrient

inputs”. The decision to focus on human impacts rather than simply the nutrient-enhancement of

selected crops or promotion of ‘nutrient rich foods’ for sale, has allowed for greater discussion of

cross-cutting issues crucial to nutrition, including gender and intra-household resource control,

food safety, disease-nutrient interactions, and even the appropriateness of metrics used to assess

agriculture-supported outcomes (ISPC 2012; CGIAR Consortium Office, 2012). As a result,

recent attempts at framing causal pathways have become increasingly elaborate as they attempt

to identify intermediate outcomes (steps in the process) on which research activities should

focus.

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For example, the framework proposed by Gillespie et al. (2012) combines the UNICEF and FAO

concepts, but it opens the door to more explicit attention to the arrows between boxes and not

just to elements within boxes. That is, the framework identifies key issues which should not be

ignored if agricultural research is to be successful, including drivers of taste in dietary choices,

seasonality, women’s health (not just the child’s) and the role of sanitation. Similarly, the

frameworks developed by Hawkes et al. (2012) and Chung (2012) elaborate some elements not

frequently highlighted, such as biomarkers of nutritional status (micronutrient deficiency) versus

anthropometry, nutrient quality (bioavailability), value chain parameters, and the creation of

demand for health services through knowledge and education.

A common factor across all such frameworks is the understanding that agriculture can influence

nutrition and health through multiple pathways (direct and indirect), and that only one of those

relates to the consumption of more food. For example, Headey et al. (2011), Gillespie et al.

(2012) and USAID (2013) talk of seven pathways, which include agriculture as the direct and

indirect (via income) source of food at household level, macro-level agricultural policy as a

driver of prices, and agriculture as an entry-point for enhancing women’s control over resources,

knowledge and status. More recently, Ruel et al. (2013) also refer to those same pathways, while

emphasizing that the number of paths is not fixed, evidence of effects along the posited pathways

is stronger for some than for others (meaning that much is still theorized rather than empirically

based), and that there are additional ways by which agriculture can support nutrition through

more distal mechanisms (supporting livelihoods, serving as programming platforms for other

sectors, buffering consumption shocks, maintaining biodiversity, etc.) that are not fully

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accommodated by the ‘7 pathway’ model. It is herein that this research seeks to bring empirical

clarity by looking specifically at CARE International’s PROMISE project in northeastern Ghana.

That said, chains of causal inferences have been woven into most analytical frameworks guiding

the search for evidence on agriculture-nutrition interactions. For example, Masset et al. 2011 lay

out a chain of connections from household participation in agriculture through direct and indirect

impacts on food and income to nutritional status. Masset et al. 2011 used this framework to

review the literature in their search for evidence of causal associations and/or plausible

mechanisms for correlations along the chain. One of their conclusions was that “only few causal

links have been successfully explored.” Given this lacuna, this research proposes to further

explore the deeper limits and possibilities of this framework by situating it within the context of

the PROMISE project in northeastern Ghana.

Hawkes et al. (2012) also used a framework, albeit a less linear one. Those authors note that

problems occur “when the links in a ‘chain of evidence’ or ‘research chain’ linking an

intervention and a nutritional outcome is not complete” (Hawkes et al., 2012). Importantly, a

lack of ‘linkage research’ aimed at uncovering mechanisms linking elements of a chain is

arguably the defining feature of all work in this domain so far. Each of the reviews of evidence

of linkages of the past decade has concluded that too many studies rely on “simplistic

associations” and too few “include all the necessary aspects of the research chain.” (Hawkes et

al., 2012). This study will endeavor to limit the level of reliance on simplistic associations to

delve into a thorough analysis of meta-data that will help bring depth to the issues illustrated in

Figure 1 through the use of existing data from GDHS, GLSS, CWIQ, CFSVA etc.

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5. Women’s control over

resources

Non-Food

spending

2. Sources of

Income

3. Food

Prices

Source of

Food

Women’s time and caring

practices Women’s own nutrition

and health

3.0 Methodology

The preliminary stage of our research is entailed two significant steps. The first phase was a

comprehensive and a systematic desk review of the policy context, project design and

implementation documents and other related literature to enable us have an informed view and

deeper insight of the PROMISE project in northeastern Ghana. The second phase entailed

extensive consultations with the Programme Coordinators, Project Managers and Field

Facilitators of CARE International who worked on the project. These consultations brought to

light a wide array of surveys, midterm reviews and evaluation reports, workshops and field

progress reports on various development issues in connection with the project under

consideration. In order not to re-invent the wheel, we made relevant use of these documents in

order to have a firm appreciation of what is possible during the field data collection process.

Figure 1: Logical Framework for Assessing the Impact of Agricultural Interventions on

Nutrition (as proposed by Masset et al., 2011) with 7 Key Pathways Added.

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In order to beef-up the desk studies, validate what was observed by others, up-date the

information, give stakeholders the chance to revise their opinions, and, above all, have a lot of

contact with the field situation to better inform ourselves - all sampled project communities were

visited to ascertain first-hand the level of impact of the PROMISE project relative to the first

three key objectives of the study. More specifically, the relevant research tools that were

employed to obtain primary data on both agricultural and non-agricultural as well as nutrition

and non-nutrition situations included a combination of methods as follows:

3.1 Data

This research made use of the 2012 baseline survey report of the PROMISE Project that is

statistically representative of the project beneficiaries in two districts of northeastern Ghana as a

sampling frame (a good basis to replicate process issues and process outcomes). We conducted a

survey using a two-stage sampling procedure, where enumeration areas were selected from all

the enumeration areas identified during the baseline survey; and then households randomly

sampled from among those listed in each selected enumeration area in the second stage. The

rationale was to mirror as much as closely the baseline before the commencement of the project

(ex-ante).

The entire survey sample was drawn from households in rural areas. We restrict our analysis to

rural households to avoid the potential misclassification of women as ‘‘disempowered’’ if they

are not engaged in agriculture. We further exclude rural households without a female adult

decision-maker, and households that were not administered the WEAI module (as was the case

for the PROMISE Project). Households with incomplete WEAI indicators were excluded,

because all 10 indicators are needed to calculate the WEAI.

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3.2 Research Design

The study design was a longitudinal study of households. Panel data was collected from the

household survey in order to measure issues bordering on productivity, women’s empowerment,

income and outcomes of project interventions. To achieve the objectives of the study, a mixed

methods approach was adopted. This approach is justified because it helps in the use of multiple

data collection tools and techniques to enhance data triangulation. The methods of data collection

were in-depth interviews, focus group discussions (FGDs), key informant interviews,

questionnaire and non-participant observation.

3.3 Sample Size Determination

The evaluation was conducted in 10 communities in the districts. A total of 250 households

comprising of 250 male and 250 female respondents constituted the sample size for the study.

The proportionate sampling technique approach, which distributes sample sizes into proportions

based on a given sample, was used. With the proportionate approach, the sample size of each

community was proportionate to the beneficiary population size of the community.

3.4 Sampling Technique and Processes

A purposive sampling technique was used to select the respondents for this study. Almost 97%

(representing 243) of the baseline participants were available for the post-ante study. Only a total

of seven respondents from both districts were replaced by collective members at the time of the

interview. The list of respondents was obtained from CARE Ghana. The list (i.e. sampling

frame) was used by the data enumerators at the community level to locate the respondents.

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3.5 Data Collection Techniques and Procedure

The study used both qualitative and quantitative data collection techniques concurrently at the

community level. A variety of qualitative participatory tools were developed to explore

contextual factors, including agency, structure, and relations and their impact on small-holder

women farmers. Qualitative tools allowed the team to capture information on norms that affect

women’s empowerment and power relationships, particularly as these factors relate to women’s

ability to actively engage in and have control over agricultural production and marketing

activities. The tools were designed to provide insight to better understand and interpret the

quantitative indicators and to help identify the key factors critical to the success of PROMISE,

including progress markers defined by PROMISE management. In addition to topical outlines,

participatory tools included ranking exercises that captured the perceived effectiveness of

PROMISE activities, wealth ranking matrix, daily activity record for women (where available),

or social gender mobility mapping tools depending on the context, were deployed.

Focus group discussions were held in all the 10 sampled communities. The focus group

discussions were conducted in English with the assistance of translators for the various local

dialects, namely; Mamprulli, Moar, Kusaal and Bisa. An average of nine beneficiaries

participated in the one - hour FGDs in all the 10 communities. Participatory methodology was

used to secure information from project participants, including their views of what is most

valuable and relevant. The focus groups were: 1) female VSLA members, 2) husbands of female

VSLA members 3) female non-members, 4) Community-Based Extension Agents (CBEAs) 5)

Male Gender Champions 6) Out-of-School Girls and 7) Nutrition Club members.

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In-depth interviews were held with executives of the District Women-Led Soya and Cowpea

Associations, male gender champions, CBEAs, participatory scenario planning (PSP)

Advisors/Facilitators and Project Facilitators in both districts. In-depth interviews lasted for

between 30 minutes and 1 hour with each category of respondents.

In addition to qualitative data collection techniques, a questionnaire was used for the household

surveys. The questionnaire was administered with smart mobile phone devices. The smart mobile

phone devices were installed with Census and Survey Processing System (CSPro version 7.1.0).

The questionnaire had 10 sections (A-J), which concentrated on identification, socio-

demographic characteristics of the respondents, female agriculture, access to productive capital,

individual leadership and influence in the community, women’s decision-making, major sources

of cash income, men’s decision-making, access to market, project achievement, sustainability

and impact. Each data enumerator interviewed 13 households representing 13 female and 13

male household decision makers. The questionnaire had 27 pages and given the short battery

life-span of the Samsung Tablets used, two households were interviewed per day by the data

enumerators.

3.6 Training of Data Enumerators and Study Piloting

A one-day capacity building workshop was held in the project districts for all the data

enumerators. The recruitment of data enumerators took cognizance of gender, at least one year

experience of using computer-assisted personal interview tools for data collection, educational

qualification (with at least a minimum of Diploma), fluency in English language and local

dialects (Kusaal, Moar, Mamprulli and Bissa). The enumerators were trained on the use of the

CSPro data collection software. The training helped the enumerators to understand the import of

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questions and the meaning of some terminologies. The training lasted seven hours because the

facilitators went through the entire questionnaire by reading question by question and explaining

unfamiliar words to the enumerators. The translation of questions into quality local dialects for

easy comprehension by the respondents was achieved. Other areas of the training workshop were

community entry and exit procedures and approaches.

The enumerators also pre-tested the tool and reported their personal experiences with the

software and reactions from interviewees. Some of the shared experiences from the enumerators

included spending three hours to complete one questionnaire, short battery life span of the tablets

etc. The challenges expatiated were addressed by the study team. These included the addition of

three extra Samsung Tablets for backup and the provision of power banks to charge tablets with

powers running low. The Research Team was on the field with the data enumerators and this

helped address challenges that came up during the questionnaire administration. The consultants

ensured that data collected were accurately done before transmission to the server.

3.7 Data Analysis

Data gathered from the field were edited and coded to ensure that all interviews were completed

and transcribed. Content analysis was done for qualitative data. This involved a matrix of

responses from key informant interviews, in-depth interviews and focus group discussions.

Themes and patterns were developed and used to explain the quantitative results. Quantitative

data were analyzed using Statistical Package for Social Scientists Version 20. The results were

also compared with international and national statistics on some variables. To measure women

empowerment, we adopted the USAID Feed the Future Women’s Empowerment in Agriculture

Index (WEAI) model.

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3.8 Scope of Study

Geographically, the scope of work covered two districts in the Northern and Upper East Regions

of Ghana (where the project was implemented in 10 communities of each of the districts). The

two districts were:

i The East Mamprusi District which is one of the 22 districts of the Northern Region of

Ghana. Located in the North-eastern part of the Northern Region; the district has

Gambaga as its capital. It is bordered to the north by Upper East Region; to the east by

the Republic of Togo; and to the West by the Gushegu and Saboba/Chereponi Districts.

The district covers an area of 3,060km2. The project’s targeted communities are:

Yunyoranyiri, Yapala, Teanoba, Bongni, La’atari, Baungu, Bongbini, Gbangdaa, Dimea,

and Jawani. The 2010 Population and Housing Census puts the District’s population at

121,009; disaggregated into 61,556 females and 59,453 males.

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Figure 2: Map of East Mamprusi District within the Context of Northern Region

ii The Garu–Tempane District is located at the South-eastern corner of the Upper East

Region. It shares boundaries with: Bawku Municipal to the South; Bawku West District

to the West and Republic of Togo to the East. It covers an area of 1,230 km2. The project

communities in this district are: Biamboog, Gozesi, Kokomada, Kpalsako, Kugasegu,

Bantafarugu, Naati, Naafteeg, Takori and Tariganga. The district’s population as per the

2010 Population and Housing Census is estimated at 130,003, disaggregated into males

62,025 and females 67,978. Agriculture is the main economic activity in the district. It

employs about 83% of the working population. The bulk of the districts’ agriculture is on

subsistence basis.

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Figure 3: Map of Garu-Tempane District within the Context of Upper East Region

The PROMISE project worked with 4, 460 direct female beneficiaries who are engaged in

activities at various stages of the soybean and cowpea value chains. The households of these

beneficiaries were the primary focus of this research. Apart from local PROMISE partner

organizations (i.e. PAS-G and PARED), institutional/organizational level stakeholders covered

during the field level activities of this research comprised of: Ghana Health Service (GHS),

MoFA (District Departments of Agriculture), District Assemblies (DAs) as well as Apex bodies

of VSLAs and Cowpea/Soya producers, processors and marketers. By way of literature, the

scope of work comprised of reviewing project documents and reports to be abreast with the

PROMISE project intervention strategy, CARE’s gender strategy, the implementation processes,

23

baseline data, monitoring and evaluation plans, project performance reports, and reports from

implementing partners.

4.0 Results and Findings

4.1 Socio-Demographic Characteristics

This section presents the socio-demographic characteristics of the respondents. The variables of

interest include household headship, gender, household size, age, marital status, highest

educational level and literacy rate.

4.1.1 Gender of Household Head

Table 1 shows the gender of household heads. The results indicate that males dominate as heads

of households in both districts. There are, however, more female- headed households at Garu-

Tempane District (GTD) – 35.2% than in East Mamprusi District (EMD) – 24.8%. The results

of the post-ante are consistent with baseline findings where it was reported that the development

may be explained by the high proportion of widow/ers at GTD compared to EMD.

Table 1: Gender of Household Head

Gender Garu-Tempane district East Mamprusi

district

Both districts

F % F % F %

Male 81 64.8 94 75.2 175 70.0

Female 44 35.2 31 24.8 75 30.0

Source: Field Survey (2018).

4.1.2 Age of Household Head

Table 2 presents the descriptive statistics of the ages of household heads. The findings show

that the mean age of female household heads is 48.4 years at GTD compared to 51.9 years at

EMD. The results also indicate that the mean age of male household heads in GTD is 47.4

compared to 48.8 in EMD. These results are consistent with baseline findings and do confirm

the preponderance of the study population to be slightly aged and less youthful (i.e. mean age

24

for both districts being 48.3 years). Contrary to age being flagged as a possible barrier to speedy

uptake of project interventions at EMD during the baseline, the findings of this research do not

readily lend credence to this view.

Table 2: Age of Household Head District HHH N Mean Std. error of

mean

SD Minimum Maximum

Garu-Tempane

MHH 81 47.35 1.822 16.399 18 72

FHH 44 48.43 2.317 15.372 23 75

Both 125 47.73 1.430 15.991 18 75

East Mamprusi

MHH 94 48.84 1.529 14.820 20 90

FHH 31 51.94 2.282 12.704 21 80

Both 125 49.61 1.282 14.338 20 90

Both Districts

MHH 175 48.15 1.175 15.543 18 90

FHH 75 49.88 1.656 14.344 21 80

Both 250 48.67 0.960 15.186 18 90

Source: Field Survey (2018).

4.1.3 Marital Status of Household Head

Table 3 illustrates the marital status of the household heads. The results show that about 70% of

household heads in GTD are married for more than 2 years compared to 78% of household

heads at EMD. This suggests that most marriages among PROMISE beneficiaries are stable and

could be a good predictor of project success. The findings also show more widow/er in EMD

than in GTD contrary to results at baseline.

Table 3: Marital Status of Respondents Marital status Garu-Tempane East Mamprusi Both districts

F % F % F %

Single 22 17.6 4 3.2 26 10.4

Married (less than 2 years) 7 5.6 2 1.6 9 3.6

Married (more than 2 years) 87 69.6 98 78.4 185 74.0

Widow/er 9 7.2 18 14.4 27 10.8

Separated 0 0.0 3 2.4 3 1.2

Source: Field Survey (2018).

4.1.4 Highest Level of Education of Household Head

Table 4 shows the highest level of education achieved by the household head. The results

25

indicate that 78% and 60% of household heads in GTD and EMD respectively have no formal

education (an average of 69.2%). In terms of formal education achieved, the findings show that

14% of the household heads in both districts have highest education up to primary level. These

findings are consistent with baseline results and cumulatively print a picture of a population

without formal education, thus negatively impacting on the speedy rate at which project

interventions could have received positive uptake.

Table 4: Highest Level of Education Achieved Education Garu-Tempane East Mamprusi Both districts

F % F % F %

No education 98 78.4 75 60.0 173 69.2

Primary 11 8.8 23 18.4 34 13.6

Junior High School 6 4.8 10 8.0 16 6.4

Secondary/Vocational/Technical 7 5.6 12 9.6 19 7.6

Tertiary 3 2.4 3 2.4 6 2.4

Non-formal 0 0.0 2 1.6 2 0.8

Source: Field Survey (2018).

4.1.5 Literacy Level of Household Head

Table 5 shows the literacy level of household heads. The findings reveal that 84% and 76% of

household heads in GTD and EMD can neither read nor write. This finding is not surprising

because majority of household heads do not have formal education as noted from baseline and

this may be a strong indication that they have not had access to non-formal education

opportunities to reverse the trend during the course of PROMISE.

Table 5: Literacy Level of Household Head Literacy Garu-Tempane East Mamprusi Both districts

F % F % F %

Can read and write 20 16.0 30 24.0 50 20.0

Cannot read and write 105 84.0 95 76.0 200 80.0

Source: Field Survey, 2018.

26

4.2 Objective 1

4.2.1 The first objective of the study was:

To investigate the extent to which the PROMISE project contributed to increased

consumption from increased food production of soya and cowpea (production-for-own-

consumption) for improved nutrition.

4.2.1.1 Dietary Diversity and Intra-Household Access

The main food preparer (typically the sampled CARE/PROMISE member) is asked to report on

12 different food groups consumed by any household member over a 24-hour period (the day

and night prior to the interview). The responses produced a Household Dietary Diversity Score

(HDDS) between 0 and 12, with the higher score demonstrating access to diverse food groups.

After determining whether any household member consumed each of the 12 food groups, the

main food preparer is asked if all, some, or no female household member over the age of 15 ate

the food item. The responses for “all women” or “some women” produce an intra-household

access (IHA) score between 0 and 12, with the higher score indicating greater access to diverse

food groups.

The mean HDDS across both districts ranges between 4.2 to 4.8 food groups at the time of the

post-ante survey, meaning households are, on average, accessing four to about five different

types of food on a daily basis (Table 6). Households in both districts saw an increase in dietary

diversity, particularly among female-headed households at GTD. Access to food diversity

between women living in female- and male-headed households moved from inequitable at

baseline to close to equitable status over the period of the project. The Post-Ante survey results

show that across both districts, food access for women, specifically, has increased since baseline,

meaning females over the age of 15 years consume more food groups than other household

27

members. The IHA pattern at EMD follows that of the HDDS; females consume fewer food

groups than other household members. During qualitative research at GTD, most respondents

asserted that the project had helped them diversify their consumption to include more vegetables,

as well as new or less-commonly used foods such as moringa or cowpea leaves. The past two

years have been unfavorable for agricultural production, so it would appear to be a positive

impact that dietary diversity and food access continue roughly consistent since baseline study.

Table 6: Food and Nutrition Security

Indicator Districts

Baseline Endline

Mean Household Dietary Diversity Scores

All Households 4.3 4.6 FHHH 3.9 4.2

MHHH 4.3 4.8

Mean Women’s Intra-household Food Access

All Households 4.2 4.0

FHHH 3.8 3.9

MHHH 4.3 4.1

Source: Field Survey, 2018.

4.2.1.2 Food Consumption Groups

The FCS is calculated based on the frequency of consumption of different food groups during

the seven days before the survey, weighted by the relative nutritional density of the food

group in terms of energy, protein, micronutrients and fat content. The eight main food groups

are: 1) main staples (cereals and tubers); 2) pulses (beans, peas, groundnuts); 3) vegetables; 4)

fruit; 5) meat and fish; 6) milk and milk products; 7) sugar; and 8) oil. Meat, fish and milk

have the highest nutritional weighting (4), followed by pulses (3). sugar (sweets) and oil have

the lowest nutritional weighting (0.5).

The frequency of consumption by food group of PROMISE households is presented in

Table 7 below:

28

Table 7: Average Days in the Past Week (7 Days) Households Consume

Food Groups

Both Districts

Garu-Tempane

East Mamprusi Food Group Average number of days consumed out of one week in lean period

FHH MHH All FHH MH

H All FHH MH

H All

Cereals and tubers 6.79 6.77 6.78 6.96 6.89 6.91 6.37 6.67 6.65

Vegetables 5.96 6.58 6.48 5.65 6.25 6.11 6.74 6.86 6.85

Meat and fish 5.71 5.98 5.94 5.73 6.03 5.96 5.63 5.94 5.91

Pulses 4.81 5.46 5.35 4.73 5.66 5.43 5.00 5.30 5.27

Oils 4.22 5.11 4.96 3.55 3.74 3.70 5.95 6.24 6.22

Fruits 3.85 3.48 3.54 3.67 3.17 3.30 4.32 3.73 3.79

Sweets 2.32 2.88 2.79 2.16 3.04 2.83 2.74 2.75 2.75

Milk 0.13 0.26 0.24 0.00 0.36 0.27 0.47 0.18 0.21

Source: Field Survey, (2018).

As expected, PROMISE households are consuming staple foods almost every day of the

week. They are also consuming vegetables, meat and fish, and pulses quite frequently. Milk

(milk, cheese, yoghurt) is the food group that is the least frequently consumed – one would

have expected the nutrition education as well as the food expos organized as part of the training

on the use of soya could have transformed consumption in this sphere, however, this did not

quite play out as confirmed by the post-ante survey results. FHHs tend to consume each food

group less frequently than MHHs except for fruits and staples. There is not much of a large

discrepancy between the consumption of food groups by districts, except for oils.

Compared to the 2012 World Food Programme’s (WFP) Comprehensive Food Security and

Vulnerability Analysis ( CFSVA), PROMISE households had a higher average frequency

of consumption of vegetables, meat and fish, pulses, and fruits (Table 8). This may be

attributed to improvements in living standards over the past three years, increased yields,

and a strengthened women’s empowerment base (economically through soya and cowpea value

chain activities).

29

Table 8 PROMISE Project FSDS and WFP CFSVA Food

Group Consumption Food groups Upper East Region Northern Region

PROMISE CFSVA PROMISE CFSVA Cereals and tubers 6.91 7.0 6.65 7.0

Vegetables 6.11 4.0 6.85 4.0

Meat and fish 5.96 3.2 5.91 4.9

Pulses 5.43 2.0 5.27 1.6

Fruits 3.30 1.9 3.79 3.1

Oil 3.70 3.8 6.22 3.0

Sweets 2.83 2.2 2.75 4.4

Milk 0.27 0.3 0.21 1

Source: Field Survey, (2018).

4.2.1.3 Food Sources

PROMISE Project households source their food during the lean season from both their own

production and from cash purchases (Table 9). Very little food is sourced from borrowing, gifts

or food aid.

Table 9: Households’ Sources of Major Food Items and Average Spent on Purchased

Amount

Food item

% of households that

sourced food item from

own production

% of households that

purchased food item

using cash

Average Spending in a Week on Food Item

for those that

purchase (GH¢)

FHH MHH FHH MHH FHH MHH

Beans & peas 29% 41% 68% 59% 4.5 5.3

Cassava 3% 8% 87% 82% 2.3 3.8

Eggs 100% 90% 0% 10% 0.0 3.9

Fish 0% 2% 98% 98% 4.0 4.2

Fresh fruits 88% 90% 6% 10% 2.0 3.2

Groundnuts 44% 67% 54% 33% 3.4 4.2

Leafy Vegetables 77% 85% 21% 16% 3.0 3.5

Maize 6% 42% 89% 57% 9.8 12.4

Meat 65% 37% 29% 60% 3.0 4.3

Milk/Yoghurt 0% 7% 100% 93% 3.2 3.0

Millet 43% 75% 55% 24% 5.5 7.2 Oil & Fats 29% 38% 71% 62% 2.4 2.2

Rice 29% 30% 71% 70% 6.3 6.1

Sorghum 60% 77% 40% 22% 6.0 7.5

30

Food item

% of households that

sourced food item from

own production

% of households that

purchased food item

using cash

Average Spending in a Week on Food Item

for those that

purchase (GH¢)

FHH MHH FHH MHH FHH MHH

Soybean 24% 21% 76% 78% 3.0 4.2

Vegetables 13% 14% 89% 92% 2.5 3.2

Yam 25% 19% 75% 78% 7.2 6.1

Source: Field Survey, (2018).

A higher percentage of beneficiaries source fresh fruits and leafy vegetables from

their own production; whereas fish, maize, soybeans and other vegetables are usually

purchased. The patterns of production versus purchasing also vary for several food items based

on the type of HH (FHH vs. MHH). FHHs tend to purchase groundnuts and millet during the

lean season to meet their consumption needs whereas MHHs tend to source from their own

production; in contrast MHHs will purchase meat during the lean season whereas FHHs tend to

mostly source from their own production. MHHs also tend to spend more money purchasing

food items overall – suggesting that PROMISE supported FHH are more self-reliant in terms of

own food production needs.

For those HHs that are not able to fully source from their own production and are

purchasing food items, the most money is spent on staple items such as maize, millet sorghum

and rice. MHHs, for example, are spending an average of over GHS12 per week

(approximately US$3) and FHHs close to GHS10 per week (US$2.3) for maize for their

families. In line with these findings on sources of food, analysis of the focus group

discussions reveals that households’ expenditure on food is higher in non-PROMISE HHs

compared to PROMISE HHs.

31

Conclusion

The above analysis of the FCS, the food consumption thresholds, food groups, and food

sources indicates that PROMISE households are within the acceptable food consumption

threshold due to a relatively varied and nutritious diet, and are able to produce enough food to

meet their household requirements during the lean season and are therefore spending less

proportion of their incomes to source these compared to non-PROMISE HHs. It is clear from

the results that increased FCSs can be achieved through a combination of increasing the

frequency of consumption and improving the nutritional value of what is consumed. The food

can be sourced from increased household production and/or increased cash for purchases. These

improvements in food consumption are most likely to be achieved through a combination of

increased and diversified agricultural production. The gap between MHHs and FHHs could

be closed through targeted support to beneficiaries in the more vulnerable FHHs.

4.3 Objective 2

The second objective was:

To determine if the project was successful in increasing income from the sale of

agricultural commodities (production-for-income) and how this translated to improved

nutrition in the household.

The project’s strategy of working with and through VSLAs was a good approach for maintaining

the functional sustainability of the initiatives set in motion. It was evident from majority of FGDs

and interviews that, VSLAs were composed of CBEAs, Input Dealers, Producers, Agro-

processors, Gender Champions and DVCC members. These actors played instrumental roles in

providing internal services. Their roles ranged from the transfer or sharing of appropriate and

32

sustainable agricultural practices; improving access (both fiscally and physically) to relevant

inputs at affordable prices at venues of good proximity; processing and sale of various value-

added commodities along the soya and cowpea value chains to members of clusters and others -

to such vital activities as, facilitating linkages for aggregators to reach buyers and processors.

One key expected outcome of PROMISE is to “increase household income for smallholder

women farmers and micro entrepreneurs through effective engagement in economic

opportunities along the soy and cowpea value chain”. PROMISE households were therefore

asked about the income earned from on-farm/agricultural-related activities as well as off-farm

activities. The total annual income was estimated by adding both income sources. In-depth

reviews and analyses of data on women in all the sampled communities indicate that their

incomes have increased in nominal terms. The contributing factors are related to increases in

yields from production, improved access to better markets, VSLA activities and profits from the

sale of value-added products along the cowpea and soya value chains (diversification of income

sources with the mean number of off-farm businesses engaged by women being 3.9).

The project’s revised M&E framework indicates that it targets to increase incomes by 50%. The

baseline reports total average annual household income for all project communities to be GHS 3,

391.03 (USD 892.41), the post-ante results suggest that average annual household incomes for all

the sampled communities increased significantly within the project period to GHS 5,666.94 (US$

1,259.322). Income growth has, however, been better for on-farm related income sources (GHS

4,719.01) than for off-farm sources (GHS 2,547.89). At the level of individual districts, a lot

1 Exchange rate as at survey period was GHS3.80 = US$1.00 2 Exchange rate of 4.54741 (www.oanda.com 16th May 2017)

33

more progress was recorded in income mobility from off-farm activities at EMD (GHS

2,190.70 = US$ 487) than at GTD (GHS 1,104.30 = US$ 245.4) (Table 11). In general terms

however, incomes from both off-farm and own production of soya and cowpeas (GHS 1,997.04)

in both districts represent a significant improvement over a baseline situation where majority

(66.2%) of FHH were not involved in soya and cowpea production and having a mean number of

off-farm businesses to be 4.1.

Table 10: Annual Household Off-farm Income by Household Headship and District

Income sources Total HHs Male headed

HH

Female headed HH

Income from off-farm activities total GHS 2,547.89 2,484.93 2,387.40

Agriculture wage labour 1,186.35 1,225.87 1,108.53

Non agriculture: wage labour 1,113.57 1,107.17 1,131.07

Skilled labour 2,173.65 2,136.74 1,732.08

Small business activities (street vending, shop

keeping)

1,152.83 1,172.70 1,176.38

Formal employee (Gov’t, NGO, private) 1,449.53 1,450.92 1,447.14

Handicrafts 571.47 386.33 412.00

Remittances (foreign, domestic) 1,141.81 153.67 106.25

Wood/charcoal sales 884.82 876.41 805.45

Non-forest timber products 173.86 175.12 168.50

Garu-Tempane 1,104.30 1,025.09 1,136.15

East Mamprusi 2,190.70 2,169.72 2,113.23

Number of off-farm businesses available to women

(mean)

4.1 3.3 3.9

% of women engaging in off-farm soy and cowpea 79.3 84.7 66.2

Small business activities (street vending, shop

keeping) %

53.3 50.1 34.2

Wood/charcoal sales (%) 27.7 23.6 28.0

Agricultural wage labour (%) 49.3 44.8 33.3

Number of soy and cowpea businesses engaged by

women (Mean)

3.6 3.4 3.8

Source: Field Survey (2018).

An examination of results of income diversification available to women by type of household

reveals an extraordinary performance or outcome between baseline and post-ante (see Table 12).

Significant strides were made by PROMISE participants in all the on-farm/agricultural income

variables considered. Income mobility within the project period increased by 210.16% (GHS

34

3197.51 or US$710.56) for all households engaged in on-farm/agricultural income generating

activities. It was more the case for GTD (GHS 4,607.45 or US$ 1,023.88) than EMD (GHS

3,629.18 or US$ 806.48). A significant result was with respect to the income growth recorded by

FHH in both districts; whereas reported incomes of this category was GHS 861.15 (US$ 190.00)

at baseline, there was quantum leap in income mobility to GHS 4306.86 (US$ 957.08) by post-

ante – representing an impressive 400% increase. There was also an impressive improvement in

the percentage of women engaged in on-farm agricultural activities compared to baseline – with

the most promising developments being all the variables considered under this category (see

Table 11).

The results from Tables 10 and 11 suggest the project beneficiaries are better off and can be

regarded as people now living above the poverty line as a result of the project intervention. The

findings show that on-farm income plus off-farm income of the project beneficiaries increased

by 114.30% (GHS7,266.90). There is, however, a higher increase (195.62%) for FHH compared

to 107% for MHH. This implies that the project has contributed massively in improving the

income levels of FHH.

Table 11: Annual Household On-farm Income by Household Headship and District

(Baseline vs Post-antes)

Baseline

Total

HHs

Male-

headed

HH

Female-

headed HH

On-farm/agricultural income[Total GH¢] 1521.50 1647.16 861.15

Crop sales (own production) 512.01 561.41 329.51

Sales of livestock and livestock products 395.91 426.45 220.00

Nursery products 150.41 173.25 48.89

Seed selling 101.87 106.24 88.08

Other 356.29 374.8 307.30

35

East Mamprusi 1694.77 1773.08 837.57

Garu Tempane 976.69 1082.18 673.16

% of women engaging in on-farm agriculture activities (Multiple response):

Crop sales (own production/household gardening) 64.3 57.1 62.6

Agriculture wage labour 19.3 14.3 18.1

Processing 17.9 9.5 15.9

Seed selling 19.8 20.6 20.0

Time spent in generating income from soy and cowpea (in

hours) 6.5 7.0 5.5

Post-ante

Total

HHs

Male-

headed

HH

Female-

headed HH

On-farm/agricultural income[Total GH¢] 4,719.01 4,931.16 4,306.86

Crop sales (own production) 2,592.12 2,661.95 2,462.29

Sales of livestock and livestock products 1,401.34 1,520.85 1,366.30

Nursery products 1,196.06 1,217.75 1,222.20

Seed selling 1,183.71 1,199.81 1,118.56

Other 1,499.15 1,412.80 1,337.51

East Mamprusi 3,629.18 3,941.33 3,507.19

Garu Tempane 4,607.45 4,773.36 4,783.04

% of women engaging in on-farm agriculture activities (Multiple response):

Crop sales (own production/household gardening) 70.3 71.2 67.4

Agriculture wage labour 32.1 25.5 28.6

Processing 26.3 25.8 34.4

Seed selling 30.6 28.8 32.4

Time spent in generating income from soy and cowpea (in

hours) - - -

Source: Field Survey (2018).

A further examination of results of improved access to markets for soya and cowpea value chain

activities as presented in Table 12 gives credence to the possibility of improved income mobility

within the project span. The mean prices of both soya and cowpeas increased well above the

prices recorded at baseline by over a 100% in both districts over the project span. With a stable

inflation rate within the project span, it is very likely that the margins realized from the sale of

these crops would have brought in above normal profits which should have translated into

improved incomes.

36

Table 12: Access to Market along Soy and Cowpeas Value Chain (Baseline vs Post-ante)

Baseline

Garu

Tempane (soy)

East

Mamprusi

(cowpea)

% reporting selling last harvest produce through:

Open market 93.8% 100%

Other buyer 6.2% -

Volume of 100kg per maxi bag of produce sold through:

Open market 75.6 160.2

Other buyer 4.3 -

Total Volume of produce sold (100kg of maxi bag) 79.9 160.2

Mean price of 100kg of maxi bag of produce sold through:

Open market 110 109.75

Other buyers 210.27 -

Mean price of 100kg maxi bag of produce during bumper season 135.94 93.21

Mean price of 100kg maxi bag of produce during lean season 259.87 126.25

% reporting difficult in getting market for their produce 30.2% 72.9%

Nature of difficulty encountered:

Low prices for products 10.3 35.8

Lack of buyers for produce 0.7 18.7

Transportation 4.4 73.9

Storage 0.7 56.7

Post-ante

Garu

Tempane East Mamprusi

soy cowpea soy cowpea

% reporting selling last harvest produce through:

Marketing committee 25.0% 23.7% 34.7% 43.4%

Open market 65.3% 47.2% 40.0% 52.8%

Other buyer 30.3% 59.2% 49.6% 40.8%

Volume of 100kg per maxi bag of produce sold through:

Marketing committee 144.81 99.11 75.33 83.55

Open market 134.57 108.73 37.20 89.08

Other buyer 151.09 80.10 14.00 74.35

Total Volume of produce sold (100kg of maxi bag) 430.36 287.94 126.53 246.98

Mean price of 100kg of maxi bag of produce sold through:

Marketing committee 230.0 440.00 205.00 410.00

Open market 220.00 400.00 200.00 390.00

Other buyers 215.00 385.00 190.00 375.00

Mean price of 100kg maxi bag of produce during bumper season 221.67 408.33 198.33 391.67

Mean price of 100kg maxi bag of produce during lean season 250.00 450.00 210.00 430.00

37

% reporting difficult in getting market for their produce 48.2% 48.7% 36.5% 51.7%

Nature of difficulty encountered:

Low prices for products 29.3% 19.3% 29.3% 35.8%

Lack of buyers for produce 31.7% 28.1% 31.7% 18.7%

Transportation 38.1% 40.2% 38.1% 73.9%

Storage 27.4% 57.3% 27.4% 56.7%

Source: Field Survey, (2018).

Conclusion

The signs of increasing food insecurity and high levels of different forms of malnutrition are a

clear warning of the urgent need for considerable additional work to ensure we “leave no one

behind” on the road towards achieving the SDG goals on food security and nutrition. Good

nutrition is the lifeblood of sustainable development and drives the changes needed for a more

sustainable and prosperous future. It is very clear from the positive nutrition outcomes being

reported under the preceding section that they did not come about solely as a result of PROMISE

beneficiaries’ own production – this is where the income growth being reported here reinforces

the idea that nutrition and income growth are not mutually exclusive. Some people argue that the

way to meet nutrition targets is to stimulate greater economic growth and higher incomes for

poor people, because malnutrition and poverty often go hand in hand. Rates of malnutrition

provide neither an independent perspective on poverty nor a basis for reducing malnutrition that

is distinct from one for reducing poverty. In general, more income leads to better nutrition over

time. Increased income usually enables poor families to get better access to the things that matter

for good nutrition: food of sufficient quantity and quality, enough time for mothers to get and use

good information on child feeding and hygiene, adequate supplies of clean water, and sufficient

preventive and curative health care of good quality.

38

4.4 Objective 3

The third objective was:

To analyse the extent to which empowerment of women agriculturists has taken place

through the efforts of the project.

Three key areas were considered in our effort to respond to this objective. These were: 1)

percentage of men and women reporting women’s participation in decision-making; 2)

percentage of men and women reporting women’s contribution on the purchase of new

productive capital; and 3) percentage of women’s inputs into household decision making.

Results of the post-ante survey on men and women reporting women’s participation in

decision-making looking at a set of 16 indicators under this domain (as shown in Table 13)

reveal that, in MHH, about two-thirds of men (69.5%) and women (72%) are reporting women’s

participation in decision-making compared to about a quarter of FHH where only 25.7% and

28.1% respectively are reporting same. It is particularly significant that men (78.2%) in MHH

are reporting meaningful participation of women in decision - making at the household level

previously reserved for men relative to issues such as: “negotiating with buyers” of their farm

produce or value added commodities along the soya and cowpea value chains. It would appear

from this result that the District Value Chain Committees (DVCCs) are doing well in terms of

facilitating the right market options for collectives thus improving their negotiation power.

On the contrary, men in FHH tend to see major improvements in women’s decision-making in

areas such as: “spending money that they have earned” (42.9%); “what inputs to buy for

agricultural production” (38.9%); and “non-farm business activity” or “whether or not to use

39

family planning” (35.7% respectively) (Table 13). Comparatively, women in MHH tend to have

a stronger participation in decision - making relative to all the issues identified with about two-

thirds of respondents (65% and above) indicating this to be true. Notable areas of over 75%

participation of women in decision-making in MHH are connected to issues of: “cash crop

farming: crops that are grown primarily for sale in market”; “livestock raising”; “negotiating

with buyers”; “children’s education” ; and “non-farm business activity” . An aggregate of

responses from both MHH and FHH suggests that only about 49% (just about half) of PROMISE

participants are convinced that women’s participation in decision - making is improving – well

below the project’s targeted 80% but well above baseline (40%). This ties in well with 51.5% of

women reporting control of their own income in the project districts at post-ante.

Table 13: Percentage of Men and Women Reporting Women’s Participation in Decision-

making Aspect of women’s participation in household

decision making

FHH MHH

%

of men

%

of women

%

of men

%

of women

Crops that are grown primarily for household food

consumption

12.5 32.9 87.5 67.1

Cash crop farming: crops that are grown primarily for

sale in market

30.8 23.8 69.2 76.2

Livestock raising 34.8 24.0 62.5 76.0

When or who would take products to the market 25.0 27.9 75.0 73.0

Non-farm business activity 35.7 24.2 64.3 75.8

What inputs to buy for agricultural production 38.9 25.9 61.1 74.1

Major household expenditures 29.7 34.6 70.3 65.4

Minor household expenditures 22.7 28.8 77.3 71.2

Negotiate with buyers 28.0 21.5 72.0 78.5

Buying clothes for yourself 31.2 31.6 68.8 68.4

Spending money that you have earned 42.9 29.3 57.1 70.7

Spending money that your spouse has earned 31.8 26.3 68.2 73.7

Children’s education 27.0 22.6 73.0 77.4

Seeking medical treatment for your children or

yourself in case of illness

30.0 32.3 70.0 67.7

Whether or not to use family planning 35.7 34.5 64.3 65.5

Participate in household finance matters 29.0 30.0 71.0 70.0

Total % 25.7 28.1 69.5 72

40

Source: Field Survey (2018).

In the second domain; “women’s contribution in the purchase of productive capital”, 12

indicators were considered in the post-ante survey. The post-ante results suggest that, whereas

more than half of women in FHH (54%) and MHH (50.1%) are reporting that their contribution

to the purchase of new productive capital is increasing, more than a quarter of their male

counterparts, 30.8% and 30.6% respectively, are reporting same. It would appear from the results

in Table 14 that, women’s contributions are strongest in the areas of: mechanized and non-

mechanized farm equipment (62.1% and 56.2% respectively); small consumer durables (56.1%);

cell phones (55.3%); small livestock (54.4%) and poultry (52.1%) – in the opinion of women in

MHH. However, for men in FHH, women’s most important areas of contribution to the purchase

of productive capital are: large livestock (43.8%); houses (39.1%) and agricultural land (38.7%).

It is conclusive from the results that, from the perspective of both genders, women are making

contributions to the purchase of productive capital in more than half of the sampled households.

Table 14: Percentage of Men and Women Reporting Women’s Contribution to the

Purchase of New Productive Capital Women’s contribution in the purchase of

productive capital

FHH MHH

% of men

% of women

% of men

% of women

Agricultural land 38.7 45.3 40.8 46.1

Large livestock 43.8 50.1 48.8 42.7

Small livestock 34.5 53.5 32.0 54.4

Poultry 33.3 50.0 34.5 52.1

Non mechanized farm equipment 30.0 57.5 30.1 56.2

Mechanized farm equipment 25.0 75.0 30.3 62.1

Means of transport 21.4 57.2 34.3 45.7

House 39.1 46.8 37.5 42.8

Large consumer durables 31.8 50.0 36.4 47.7

Small consumer durables 27.1 58.3 27.6 56.1

Cell phone 14.3 52.4 16.1 55.3

Other land not used for agricultural purposes 30.0 51.6 38.3 39.3

Total 30.8 54 30.6 50.1

41

Source: Field Survey (2018).

The third area of investigation was with respect to “women’s input into household decision-

making”. A set of 16 decision-making markers were identified for households to gauge women’s

input according to the following Likert scale: 1) Input into some decisions; 2) Input into most

decisions; and 3) Input into all decisions. “Input into all decisions” represents the best desired

state.

Results of the post-ante survey indicate the following:

• At GTD, women make “input into all decisions” relative to “buying clothes for

themselves” (45.8%) and “spending money that they have earned”(40.2%) – with more

than a third of respondents indicating this to be true. A similar trend is observed for EMD

where more than half of women make “input into all decisions” relative to “buying

clothes for themselves”(54.9%) and “spending money that they have earned”(58.2%)

(Table 15).

• The areas where project participants “make input into most decisions” are: “what inputs

to buy for agricultural production” (42.1%) and “livestock raising” (39.8%) for the case

of GTD. However, at EMD, “crops that are grown primarily for household food

consumption” (50.4%) and “whether or not to use family planning” (51.6%) were the

issues highlighted by more than half of women responding to the survey (Table 15).

• The areas where women make “input into some decisions” were identified at GTD to

include: “non-farm business activity” (42.5%) and “whether or not to use family

planning” (36.6%). In the case of EMD, “spending money that your spouse has earned”

(34.3%) and “Livestock raising” (32.4%) were flagged to be the areas of least input into

42

decision-making (Table 15).

These results clearly point to the fact that, while PROMISE participants are getting empowered

with time, they still lag in many vital areas of decision-making power such as: decisions on crops

that are grown primarily for sale in the market by both men and women; raising of livestock;

spending money that their spouses have earned; and when or who would take products of men to

the market. It is however, significant to note that, the results of the post-ante survey reveal

significant improvement over baseline where only about 30% of women were recorded to have

influence in household decision-making relative to the issues itemized.

Table 15: Women’s Inputs into Household Decision-making Decision making domains Garu-Tempane district East Mamprusi district

Input into

some

decisions

Input into

most

decisions

Input into

all

decisions

Input into

some

decisions

Input into

most

decisions

Input into

all

decisions

Crops that are grown

primarily for household food

consumption

28.0

36.8

31.2

28.2

50.4

17.9

Cash crop farming: crops that

are grown primarily for sale in

market

30.5

33.7

27.4

29.4

47.1

17.6

Livestock raising 29.1 39.8 20.4 32.4 39.8 19.4

When or who would take

products to the market

31.1

27.4

31.1

31.6

44.9

16.3

Non-farm business activity 42.5 27.5 20.0 20.0 41.4 25.7

What inputs to buy for

agricultural production

29.0 42.1 22.4 29.8 46.2 16.3

Major household

expenditures

32.1 33.0 29.5 28.9 35.1 24.6

Minor household

expenditures

30.2 30.2 37.1 22.9 44.1 31.4

Negotiate with buyers 24.3 35.5 34.6 17.4 46.7 21.7

Buying clothes for yourself 18.7 31.8 45.8 3.5 39.8 54.9

Spending money that you

have earned

23.2

32.1

40.2

4.5

36.6

58.0

Spending money that your

spouse has earned

25.2

31.1

24.3

34.3

39.4

9.1

Children’s education 25.5 35.5 37.3 17.2 37.1 40.5

Seeking medical treatment for

your children or yourself in

case of illness

26.6

33.9

37.6

20.8

40.0

20.1

Whether or not to use family

planning

36.6 28.2 26.8 10.9 51.6 29.7

Participate in household

43

finance matters 33.8 27.5 31.2 22.3 42.7 26.2

Source: Field Survey (2018).

Conclusion

The results in this section strongly support the conclusion that PROMISE women beneficiaries

have increasingly enjoyed a degree of economic and social empowerment, progress and positive

change. VSLA activities, as a complementary strategy to nutrition education, have undoubtedly

contributed to women’s increased participation in decisions about producing and expending

household income as well as decisions about roles and divisions of labour within the household

and participation outside of the household. Communities have experienced enhanced discourse

about patriarchal roles, relationships, and practices. Women cite their involvement in PROMISE

as a gateway toward more equitable household decision-making and a greater voice inside and

outside of the household. But this is a long process; PROMISE has only begun this process.

4.5 Objective 4

The fourth objective of the study was:

To proffer recommendations on agriculture and nutrition policies for improved household

level consumption of soya and cowpea, individual food and nutrient intake and nutrition

status.

Overall, the FGDs held with majority of project stakeholders gave strong indication that the

target communities feel that the project has been successful in meeting their immediate needs for

food (good nutrition), income (VSLAs) and the underlying causes of vulnerability to male

exploitation through gender discrimination, stereotyping and exclusion. There is strong

indication that the objectives of PROMISE are still highly valid and relevant. This is evidenced

both by the external environment – the continuously growing number of national and

44

international NGO’s and CSO’s programming in this space since PROMISE began. Examples

abound such as the USAID’s Resilience in Northern Ghana (RING)3 and Strengthening

Partnerships, Results, and Innovations in Nutrition Globally (SPRING)4 projects in Northern

Ghana. The relevance of PROMISE project is further appreciated through it responsiveness to

the current and ongoing needs of beneficiaries as clearly spelt out in the District Medium Term

Development Plans (DMTDPs) of East Mamprusi and Garu-Tempane Districts. The DMTDP

(2014-2017) of East Mamprusi, for instance, reports that “the district continues to measure a

reduction in low birth weights (LBWI babies due to a number of interventions: malaria control in

pregnancy (supported by EPPICS); Nutrition and Malaria Control for Child Survival Project (NMCCSP)

and CARE’s PROMISE project. Therefore the significant reduction in the LBW babies may have been

contributed by these interventions. Such initiatives need to be expanded to cover more communities”

(see p.55 of EMD MTDP, 2014). Similarly, in Garu-Tempane, the DMTDP spells out efforts to

“train 160 farmers groups in nutrition education and meal planning using soya and cowpea in

consonance with CARE’s PROMISE model” (see p. 210 of the GTD MTDP, 2014). These

developments clearly indicate the project is aligned to the strategies and policies of the District

Assemblies in the project area and therefore is contributing to value addition by way of local

nutrition development needs and aspirations (Impact pathway 1).

Drawing from the performance of the project and wide consultations with beneficiaries and key

local institutional level stakeholders, the most promising results in terms of increased

3 The USAID/Ghana Resiliency in Northern Ghana (RING) program is an integrated project and partnership effort under USAID’s Feed

the Future initiative designed to contribute to the Government of Ghana's efforts to sustainably reduce poverty and improve the nutritional status of vulnerable populations. The purpose of the RING project is to improve the livelihoods and nutritional status of vulnerable households in targeted communities of 17 districts in the Northern Region. This is being achieved through three complementary project components:

increasing the consumption of diverse quality foods, especially among women and children; improving behaviours related to nutrition and hygiene of women and young children; and strengthening local support networks to address the ongoing needs of vulnerable households. 4 The Strengthening Partnerships, Results, and Innovations in Nutrition Globally (SPRING) project seeks to strengthen global and

country efforts to scale up high impact nutrition practices, prevent stunting and anaemia in the first 1,000 days and link agriculture & nutrition. SPRING is funded by USAID under a five-year cooperative agreement at the intersection of the U.S. Government’s two flagship foreign

assistance initiatives—Feed the Future and Global Health Initiative

45

consumption of soybean and cowpea by women were galvanized through the Community Food

Demonstration or Exhibition Bazaars/Durbars. Using the Community-based micro finance

schemes commonly known as the Village Savings and Loans Associations (VSLAs) as conduits

to improve nutrition education proved to be effective platforms for easily reaching women with

skills and techniques for adding value to soya and cowpea. The approach was found to be

women-friendly, women-dominated (usually 80% to 95%) and self-sustaining that afforded and

enhanced access to nutrition information aside the direct financial security it offered to project

beneficiaries. The VSLAs and Community Food Demonstration or Exhibition Bazaars/Durbars

presented unique opportunities in terms of equitable participation of women and girls in the

soybean and cowpea value chains. Complementing these achievements were the women-led

platforms for soya and cowpea VCs (Agbadeeya Ma and Garu Farmers’ cooperative) which

were envisaged to galvanise Area Councils (ACs), District Assemblies (DAs) and Produce

Buying Companies’ support for the production, processing and marketing of soya and cowpea

produce and products. These platforms have a huge potential to revolutionize women’s

participation in the soy and cowpea VCs and improve nutrition outcomes. The visionary

decision to support beneficiaries with soya threshing machines to improve their labour savings

has been useful but the timing for the delivery of the machines was less than ideal and this has

by default created a lacuna in appreciating the effectiveness of the Operation and Management

Committees (OMCs) set up to oversee their operations (Impact pathway 2).

Another approach that improved the production capacity of women to increase yields in order

that more soya and cowpea could be available for household consumption was the Farmer Field

and Business Schools (FFBS). This approach uses demonstration plots at the community level

to experiment with different good agricultural practices, the results of which are evident to

46

women beneficiary farmers. The FFBS approach covers knowledge transfer to mostly women in

the areas of sustainable agriculture, market, nutrition, gender and monitoring and evaluation

using participatory processes. The fact that FFBS plots are established at community levels

allows greater participation of women in the demonstrations for improved soya and cowpea

production. The use of Community-Based Extension Agents (CBEAs, solely women) to

facilitate extension delivery especially to small holder women farmers at the community level

complemented well the activities in respect of FFBS. Using women CBEAs for the FFBS is a

good strategy that can improve women’s equitable participation in the soy and cowpea value

chains - strategically linking these CBEAs to on-going CARE projects or other related donor-

funded projects in the PROMISE operational districts will go a long way to sustain nutrition

outcomes leveraged through the project (Impact pathway 3).

Some evidence exists of communities and households in PROMISE target communities showing

ownership of project activities, willingness and capacity to sustain project outcomes. Evidence of

sustainability includes the registration of umbrella bodies to support VSLAs in East Mamprusi

and Garu-Tempane through the District Departments of Cooperatives as well as the Ghana Rural

Enterprises Programme. VSLAs registered with these apex bodies are guaranteed of continuous

support of the programme through the Local Business Associations (LBA) registration

procedure. Through this procedure, VSLA members are able to access the Rural Enterprises

Development Fund (RED Fund) and a Matching Grant to support the up-scaling of their

businesses along the soya and cowpea value chains (in all cases, beneficiaries are supported with

start-up kits to facilitate their take off as local enterprises).

The project’s networked structure granted access to inexpensive vehicles to multiply their reach.

The structure included two locally-based organizations as implementation partners, government

47

agencies as technical partners (GHS, MoFA, DAs etc.) and collaborators like the Savannah

Agricultural Research Institute and the University for Development Studies, with a shared goal

of addressing problems of nutrition among women, girls and boys. PROMISE’s strategy to

project delivery, which emphasized capacity building and community mobilization to empower

women so they can address their own problems, supported the sustainability of project outcomes.

Training and joint planning are strategies PROMISE employed to influence the practices of

CBEAs, Male Gender Champions, Community Nutrition Volunteers, Soya and Cowpea

Processors, Producers and Marketers operating in the project districts. Uptake of soya and

cowpea nutrition information at this level is important as contact with communities is direct.

However, unstable funding, competing demands and lack of access to refresher training can

hamper sustainability in the absence of PROMISE (Impact pathway 4).

Without further interventions (PROMISE or otherwise), communities’ abilities to sustain

livelihood benefits and gains in gender equality could be at risk. Gender-related results of the

project, including improved confidence of women, access to financial capital through savings

and loans groups and economic independence through participation in small business activities,

are significant. However, persistent challenges like disparities in education levels among females

and males (both project districts) and rigid gender roles can keep women in a vulnerable

position: women take on new roles in addition to the ones they already have and men have

reduced incentives to contribute to household expenses as a result of their knowledge of the

economic empowerment women have received from the project. It was reported during FGDs

that, some men are now taking advantage of their awareness of women’s economic

empowerment through the project to deny them of “chop money” (money that is usually

provided by male household heads for expenses related to family upkeep).

48

As noted earlier, the fact that some PROMISE nutrition education and approaches are finding

expression in the DMTDPs of both districts gives significant indication that opportunities abound

for the replication of some methods and tools of the project through the decentralized structures

of the Assemblies, namely; GHS, DDA, Business Adviory Centers of the Ghana Rural

Enterprises Program etc. There were countless reported cases during the FGDs in the project

communities about the sharing of soya and cowpea recipes with other communities other than

those of PROMISE. It is also envisaged that when the women-led platforms established by the

project become fully operational, their membership base could go beyond only PROMISE

beneficiaries – there is thus an opportunity for the replication and out-scaling of PROMISE

methods, tools and approaches (impact pathway 5).

5.0 Conclusion

Overall, PROMISE’s evidence of pathways to impact is quite strong. The project has achieved

considerable pathways to impact at the household, community and district levels. Impacts at the

household level are perhaps the greatest and provide the strongest evidence of how the lives of

beneficiaries have changed as a result of their direct participation in the project. They include

evidence of improved nutrition, strengthened and diversified livelihoods (through skill

acquisition for processing and marketing soya and cowpea products), improved agricultural

practices and access to physical, financial, social and human assets, improved protection of key

assets and shifts in gender dynamics that foster and promote women’s agency. Where challenges

and barriers to impact were encountered, contributing factors included mostly complex attitudes

and perceptions deeply embedded in culture, custom or religion.

49

Over the course of the four year project span, it has successfully met its purpose and significantly

contributed to nutrition outcomes. The project has contributed to the district and national

discourse on how to achieve Gender-Sensitive Livelihood Security; it has examined the extent -

and the results - of PROMISE’s influence with respect to increasing consumption of processed

soya bean and cowpea and products; how vulnerable women and girls can equitably participate

in and benefit from soya bean and cowpea value chains; and how to influence District Assembly

processes in the two districts to support women-led multi-stakeholder platforms for cowpea and

soya bean value chain activities. PROMISE has in important ways redefined and deepened the

understanding – and use – of soya bean/cowpea as an approach to improving nutrition outcomes

without being prescriptive, by providing adaptable or flexible strategies that have respect for

local dietary recipes.

At the district level, the project’s willingness to work with others and the ability to coordinate a

‘basket of collaborators’ to better serve the needs and interests of project communities is

commendable. In addition to strengthening the capacity of local government services (i.e.

Planning Units of the District Assemblies, Ghana Health Service, District Departments of

Agriculture and agricultural extension staff for example), PROMISE also engaged a number of

new service providers including radio stations and private hospitality industry actors in learning

about and disseminating knowledge on soya and cowpea recipes or diets more widely. In East

Mamprusi for example, the PROMISE project is considered the ‘teacher’ of soya recipes as a

result of its learning events and various trainings hosted together with other local institutions.

Project communities feel more empowered and are more mobilized through such groups as the

VSLAs, to lobby government and ask for resources using their CBEAs. In terms of improving

50

local institutions’ access to soya and cowpea nutrition information, PROMISE’s focus was on

the use of Nutrition Counselling Cards and improving access to such. Packaging nutrition

information in such a way that can be easily consumed by beneficiaries has raised general

awareness of the uses and benefits of soya and cowpea recipes. An important pathway worth

policy consideration is how to improve knowledge, understanding and awareness of longer-term

benefits of sustained reliance on cowpea and soya recipes for optimal health benefits.

6.0 Recommendations

Based on the findings of the study, this section provides recommendations for either an extension

of the current project or new projects based on the PROMISE model. Some overarching themes

and patterns across PROMISE districts contribute to the reflections presented as suggestions

below:

1. Cooking demonstrations have proven to be very effective mechanisms to introduce

nutrition concepts as well as teaching beneficiaries on how to prepare food in better

hygienic conditions using local ingredients and recipes. This is a positive departure from

traditional training and assistance in nutrition that provide external packages where

supplementary food is provided. It is recommended that more integrated work within the

health sector is engineered through health workers and other stakeholders using soya and

cowpea recipes based on the PROMISE model anchored to the following change levers:

• Capacity – improved knowledge, skills, relationships, self-confidence, and

conviction of women farmers;

• Access – increased access to productive resources, assets, markets, and

appropriate and reliable services and inputs for poor women farmers;

51

• Productivity and Incomes – improvement in yields and incomes through adoption

of sustainable and intensified agriculture and value addition using the Farmer

Field and Business School (FFBS) model;

• Household influence – increased poor women farmers’ contributions to and

influence over household income and decision-making; and

• Enabling environment – more positive and enabling attitudes, behaviours, social

norms, policies, and institutions.

2. Considering the low level of literacy of women beneficiaries in VSLAs or SMEs (under

the PROMISE project); managing their operations and benefits, require the provision of

functional literacy and alternative adult education and may be worth considering for

future programming. As this component may be costly, the development of partnership

with existing governmental programmes such as the Rural Enterprises Programme (REP)

or the National Entrepreneurship and Innovation Programme (NEIP) could be a

worthwhile effort towards guaranteeing their functional sustainability as critical arenas

for nutrition education. VSLAs are a vital entry point for nutrition information

dissemination; however, the importance of linking VSLA groups to Microfinance

institutions with adapted financial services (interest rate, repayment period) to ensure

their financial inclusion is not receiving much policy support within government circles.

It is necessary that government’s financial inclusion efforts take cognizance of this lacuna

and institute measures to make this a reality.

52

3. In a context of chronic food shortage, the combination of several approaches is most

appropriate. Addressing the problem of malnutrition (sensitization to improve nutrition

practices, diversification of food consumption) while developing productive and income

generating interventions using soya and cowpea are improving the long term availability,

accessibility and proper utilization of food by beneficiaries as witnessed under the

PROMISE project. Given that both of these strategies have resulted in strong changes in

agency and structure, it is suggested that future government projects adopt, articulate and

consolidate a clear and specific government engagement strategy in which agencies are

clearly identified; an activity plan and key gender equality messages are developed and

milestones are set for all stakeholders. Therefore, supplementary resources in terms of

capacity building and skilled technical staff be dedicated to this where necessary.

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Acknowledgement

The research leading to these results has received funding from the UDS/UNICEF Ghana Inclusive

Development Research Network (GIDRN) initiative to support research on inclusive development in

Ghana. The authors are solely responsible for all omissions or deficiencies. Neither UDS/UNICEF nor the

GIDRN are accountable for the content of this paper.