Nutrition Sensitivity of Smallholder Agricultural Production in Northwest Ethiopia

doi:10.21203/rs.3.rs-2821487/v1

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Nutrition Sensitivity of Smallholder Agricultural Production in Northwest Ethiopia

https://doi.org/10.21203/rs.3.rs-2821487/v1

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Background

Nutrition-sensitive agriculture is a production approach to the ensure production of a variety of affordable, nutritious, culturally appropriate, and safe foods in adequate quantity and quality to meet dietary requirements. The objective of the study was to assess the nutrition sensitivity of smallholder agriculture.

Methods

The study was conducted in four districts of northwest Ethiopia. Data were generated from 748 randomly sampled households using a structured questionnaire-based survey. The analysis was performed using the production diversity score and Simpson’s Diversity Index of food groups produced. A multiple linear regression model was employed to identify factors affecting the production of diversified food groups.

Results

The study revealed that smallholder households on average produce 6.08 food groups out of 12. The production diversity index of smallholder food production is also found to be 88.6%. Multiple linear regression analysis results, on the other hand, shows that the sex of the household head, year of schooling, farming experience, number of oxen, contact with agricultural extension worker, irrigation use, and availability of animal feed are statistical significant factors positively affecting on-farm production diversity of smallholders. Conversely, the age of the household head negatively affected production diversity.

Concluding Remarks:

The study concludes that smallholder agricultural production in northwest Ethiopia is nutrition-sensitive and can supply minimum dietary diversity to households. Promoting small-scale irrigation schemes and strengthening nutrition-sensitive agricultural extension services could contribute to food and nutrition security.

Nutrition & Dietetics

Food Science & Technology

agriculture

diversity

nutrition

sensitive

smallholder

Interventions of food and nutrition to produce productive generation for sustainable development focus on tackling the immediate, underlying, and basic causes. Nutrition interventions imposed by technical experts and policy issues based on evidence generated are ongoing [1]. These interventions are broadly classified as nutrition-specific and nutrition-sensitive [2, 3]. Nutrition-sensitive interventions focus on complementary sectors including agriculture, health social protection, education, water, sanitation, and any other relevant to affect the underlying determinants of food and nutrition security, poverty, and scarcity of resources among others [4, 5].

Agricultural programs and projects are important components of nutrition-sensitive interventions. Nutrition-sensitive agriculture (NSA) is stated as an approach that seeks to ensure the production of a variety of affordable, nutritious, culturally appropriate, and safe foods in adequate quantity and quality to meet the dietary requirements of populations in a sustainable manner [6, 7]. NSA aims to maximize the positive impact of the food system on nutrition outcomes [8, 9]. It places a nutrition lens on the food and agricultural sector as a whole without undermining its own goals to achieve food security and good nutrition [7]. However, historically, the goal of agriculture was focused on increasing production and improving income.

Making agriculture and rural development projects nutrition-sensitive is relatively new and positions several challenges, and gaps to the general approach for effective interventions [10, 11]. Nutrition-sensitive agriculture to impact better nutritional outcomes need to follow certain pathways [12]. The pathways include agricultural food production (production pathway), agricultural income (income pathway), and women’s empowerment [13–15]. There are also additional pathways suggested that include nutrition-related knowledge, and strengthening local institutions [16]. Depending on the context, the pathway to nutrition-sensitive agriculture could also consider the food environment in the market, natural resources management, water, irrigation, health, and sanitation [17].

The production pathway of agriculture for better nutritional outcomes focuses on diversified and nutrient-dense crop production including animal products such as dairy, poultry, meat, and fish production. Availability and access to diversified nutrient-dense food through production pathways at the smallholder farm household level are performed mainly for own consumption [18, 19]. Smallholder production diversification is also adaptive and cost-effective risk reduction strategy [20–22]. The production pathway of agriculture is linked with the available assets of the households and agricultural-based livelihoods [23]. Measuring agricultural diversity as an indicator for nutrition sensitivity requires assessing crop and farming diversity that is the number of crops grown and the number of overall farming activities including livestock husbandry [24]. Looking into existing practices and building upon such experiences to improve the food and nutrition security of communities and societies is seldom considered. This study is aimed to assess existing practices of nutrition sensitivity of smallholder agricultural production in northwest Ethiopia and factor affecting plant and animal origin food production diversification.

The study was conducted in North West Ethiopia represented by four districts, namely, Alefa, north Achefer, Takusa, and Quara. The study area has an estimated population of 814,021 which include both rural and urban dwellers. There are about 130,472 registered smallholder farm households, which are expected to feed their households and supply surplus food to the growing rural population from fragmented lands. A cross-sectional study consisting of quantitative and qualitative techniques was employed. Data were generated from randomly sampled 478 smallholder households through a household survey. The structured questionnaire was used to catch demographic, socio-economic, and institutional attributes, types, and quantities of agricultural commodities produced.

Agricultural commodities produced by the smallholder were categorized into 12 food groups based on the recommendation of FAO and FANTA guidelines of dietary assessment [25]. The analysis was performed using production scores (based on count), diversity index, and multiple linear regression analysis. Farm production diversity was calculated using Simpson’s Diversity Index (SDI). There are various types of diversity indices used in different empirical investigations, largely in ecological studies. Abundance models which include geometric series ranked abundance list, negative exponential distribution, log-series, and log-normal distribution models among others. On fitting abundance distribution model and diversity indices derived from abundance distribution like refraction method and Hill’s diversity number. However, these models focus on the abundance of species (food group in our case) based on probability distribution. SDI is chosen because of its relative advantage of showing both richness or abundance and evenness or relative abundance. The evenness of the food group (Fi) is estimated as:

Fi = Ni/N, where Ni is the abundance of i^th food group in the sample and

Where n is the number of food group

The diversity index was estimated as:

D = 1 - n (n-1)

N (N-1) where n= production or dietary score of each food group, and N= total production or dietary scores from all food groups.

The index is a proxy indicator for food group richness, which is the total score of different the food groups in a sample and food group evenness, which is a relative abundance of each food group. The food group richness is a measure of the total number (count) of food group produced on the farm of smallholders. The food group evenness, on the other hand, is the proportion of each food group produced by smallholders relative to all other food groups. A multiples linear regression model was used to identify factors affecting aggregated production diversity.

Study Variables

Farm production diversity measured in total production score at the household level is the dependent variable of the study. It is the score (total count) of food groups produced at the smallholder farm households level out of 12. Demographic and various socio-economic variables including the age of the household head, sex of head of the household, year of schooling of the head of the household, farming experience, arable land, number of oxen owned, number of contacts with agricultural extension workers, number of family members under productive age group, use of irrigation, membership of any locally available cooperatives and consideration management difficulties were hypothesized to be independent variables affecting production diversity of smallholder farm households.

Smallholder Production Diversity

Farm production diversity of smallholder households was assessed taking agricultural commodities emanating from both crop and livestock components. It was used as an indicator of the economic capability of diversified food at the household level that smallholder agriculture is contributing. Irrespective of the quantity produced; smallholder households in northwest Ethiopia on average produce 6.08 food groups annually with a standard deviation of 2.13. The average farm production diversity of smallholders in northwest Ethiopia is adequate to avail the minimum daily diet diversity recommended by the Ethiopian Food-Based Dietary Guideline [26]. The maximum food group produced at the household level is found to be 11 per annum. 96.83% of smallholder household produce at least three food groups combined from plant and animal sources with modal food groups of 6 per household in a single main production season.

Only 40.6% of smallholder farm households produced agricultural commodities constituting 7 and more food groups and 59.42% 6 food groups more in the area studied. The smallholder households with farm production diversity of 6 food groups constitute 18.83% followed by the proportion of farm households who produced 4 and 7 food group representing 17.78% and 16.53% respectively.

Table 1

Number of food groups produced by smallholders (n = 478)
No. of Food Group	Freq.	Percent
one	3	0.63
two	12	2.51
three	30	6.28
four	85	17.78
five	64	13.39
six	90	18.83
seven	79	16.53
eight	42	8.79
nine	40	8.37
ten	23	4.81
eleven	10	2.09
Total	478	100.00

Simpson’s index of diversity was used to estimate the farm production diversity of smallholders measured in food groups. The index was used as an indicator for food group richness, which is the total score of different food groups in a sample and food group evenness, which is a relative abundance of each food group. Accordingly, the results of food group richness analysis show that cereals, meat, and vegetables respectively constitute 16.07%, 16.45% & and 13.46% of production scores out of total food groups from annual production of smallholder farm households. Irrespective of the quantity, the share of egg and oilseed production form all annual food groups produced constitute 11.57% and 8.09% respectively. Whereas milk and its products account for 7.23% of the total food group production share at the smallholder household level and followed by tubers and root crops which constitute a 6.33% share of food groups produced. On the other hand, spices and condiments constitute 2.82% of the farm production diversity of smallholders. The share of honey/sweets from all food groups produced annually is found to be 2.48% and followed by fruits and fish production that constitute 2.38% and 1.1% farm production diversity share from all food groups produced annually.

By aggregating all crop and livestock commodities, the overall farm production diversity of smallholder households was also calculated using SDI. As a result, the farm production diversity index (FPDI) is found to be .886 (88.6%) in smallholder households of northwest Ethiopia. This implies that from randomly drawn two agricultural products at the household level, the probability of getting products from different food groups is 88.6%. In another way, from randomly drawn two agricultural products in the household, the probability of getting these commodities from similar food groups is 11.4%. However, the amount of some food groups produced at the household level might not sufficient to meet the quantity required to feed all the household members.

Determinants Of Production Diversity

Smallholder agricultural production is affected by biological (herbs, pests, insects and diseases causing microorganisms); climate variables (rainfall pattern and intensity, wind, and floods); soil fertility, and inputs including agricultural technologies. However, only demographic, socioeconomic and technological variables such are irrigation were considered to see effects on farm production diversity of smallholder households.

Using a count of production scores out of 12 food groups as considered as a response variable, and 13 explanatory variables, a multiple linear regression models was run. The result of the analysis shows that eight explanatory variables include age of the household head, sex of the household head, year of schooling of the head of the household, the farming experience of a household head, number of oxen owned, number of contacts with agricultural extension workers, use of irrigation, and availability of animal feed are statistically significant variables positively affecting farm production diversity of smallholders.

As shown in the table.2, the regression output indicates that holding other factors constant, a year increase in the age of the household head decreases farm production diversity by 0.04 at a 99% of the confidence interval. However, the sex of the household head has a statistically significant positive effect on farm production diversity. Compared to female-headed households, male-headed households make 0.94 more farm production diversity at a 99% of the confidence interval. Similarly, years of schooling of the household head has also a positive impact on the farm production diversity. For each additional year of schooling of the household head, the farm production diversity increases by 0.07 at a 99% of the confidence interval. Likewise, farming experiences and the number of contact with agricultural extension workers have also been positively associated with farm production diversity. Each additional of year of farming experiences and contact with agricultural extension worker results in increases in farm production diversity of smallholders by 0.05 and 0.07 respectively statistically significant at a 99% of the confidence interval.

Table 2

Factors affecting farm production diversity (n = 478)
Total Production Score of household (tpsh)		Coef.		St.Err.		Sig
Age of household head		− .044		.016		***
Sex of household head		.942		.25		***
Year of schooling		.074		.026		***
The arable land of household		− .028		.042
Farming experience		.051		.016		***
Number of oxen		.301		.066		***
Distance to market		.039		.031
No. contact with DA		.070		.026		***
No. productive family members		− .011		.054
Use of irrigation		.891		.263		***
Availability of animal feed		.513		.239		**
Cooperative membership		.158		.196
Consideration of management		− .049		.189
Constant		4.556		.468		***
Mean dependent var	6.079		SD dependent var		2.129
R-squared	0.224		Number of obs		478
F-test	10.314		Prob > F		0.000
Akaike crit. (AIC)	1984.768		Bayesian crit. (BIC)		2043.143
* p < .01, p < .05, * p < .1

Given its multiple roles in agricultural production, ox ownership has a positive effect on farm production diversity. Moreover, the model result demonstrates that an additional ox in smallholder farm households increases farm production diversity by 0.30 which is statistically significant at 1% probability. Irrigation schemes, be it small or large scale, are found to be important infrastructure positively affecting diversified production of farm households. The linear regression analysis affirmed that irrigation user farm households make 0.89 more farm production diversity compared to nonusers statistically significant at 1% probability. As it is the major determinant of livestock production, the availability of affordable animal feed has also positively contributed to farm production diversity. Smallholder farm households who have access to affordable animal feeds make 0.51 more diversified agricultural products. However, the arable land of the households and the number of family members under the productive age group are negatively associated with farm diversity but not statistically significant. Though, it is not statistically significant, distance to the nearest market center and memberships to locally available cooperatives are also positively associated with the farm production diversity of smallholders. The finding has consisted with similar research conducted by Mussema et al (2015) in Oromia regions of Ethiopia that agricultural diversification is determined by household asset ownership and agricultural extension services among others.

Smallholder agricultural production in northwest Ethiopia is nutrition-sensitive. Farm production diversity in small and fragmented land is capable of supplying a diversified diet to the household from their own production. Regardless of the effect of biological, climatic, and ecological variables that might affect production quantity and quality, promoting irrigation schemes, nutrition-sensitive agricultural extension using nutrition social behavioral change community (NSBCC), and investment in animal feed production using available resources could improve household economic access to diversified diet and hence contributes food and nutrition security. As far as human existence and the question for development persist, the journey towards meeting food and nutrition related goals is endless. Therefore, continuous evidence generation on existing community-based alternative way of tackling the challenge of food and nutrition insecurity is crucial.

Ethics approval and consent to participate

Prior to staring data collection, the objective of the study and its nature was explained in written consent form attached to the questionnaire. Befits and risks of the study, and confidentiality of information were well explained. No false promises, such as compensation, were given. The participation to the study was based on voluntary participation. Data were collected after security consent from participants. Study participants were acknowledged.

Consent for publication

Not applicable

Availability of data and materials

Not applicable
Competing interests

The authors declare that they have no competing interest.
Funding

Bahir Dar University and Urban Agriculture for Advanced Healthy Food Systems in Ethiopia, funded by IDRC, partially supported for data collection.

Authors' contributions

Genanew Agitew participated in developing proposal, supervision of data collection, data entry and analysis, drafting, and revising the manuscript. Zewdu Berhanie and Samson Gebremedhin, were also involved in data analysis, data collection, and commenting the draft and revised the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We would like to thank Bahir Dar University and Urban Agriculture for Advanced Healthy Food Systems in Ethiopia funded by IDRC, Canada, for their small financial support and the University of Gondar for the support during data collection. We also would like to appreciate enumerators and participants of the study.

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The study has been approved by Bahir Dar University Institutional Review Board.

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Nutrition Sensitivity of Smallholder Agricultural Production in Northwest Ethiopia

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Abstract

Background

Methods

Results

Concluding Remarks:

Introduction

Methods

Study Variables

Results And Discussion

Smallholder Production Diversity

Determinants Of Production Diversity

Conclusion

Declarations

References

Additional Declarations

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