The role of homestead fish ponds for household nutrition security in Bangladesh

Abstract

This paper examines whether income from homestead aquaculture contributes to household nutritional outcomes in developing countries. We used data from 518 homestead aquaculture producers in Bangladesh. We applied a two-stage least squares (2SLS) as well as a three-stage least squares (3SLS) model in a simultaneous equations framework to estimate the effects of aquaculture income on household food consumption and dietary diversity. Homestead aquaculture increased household food consumption and improved dietary diversity by generating additional cash income and stimulating higher fish consumption from home production. Moreover, income from aquaculture helped poor farmers to improve the quality of householder diets by purchasing more calories from the market associated with protein rich and energy-dense food items. Our results have important policy implications for countries with low dietary diversity such as Bangladesh. As Governments tend to undervalue home production by the poor, we emphasize that homestead fish production remains important for many low-income households. Therefore, the Department of Fisheries in Bangladesh should reconsider its view on the role of homestead pond production and give it more recognition in its extension activities.

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Notes

  1. 1.

    The remote sensing technology excluded very small ponds (which account for a large portion of those found in rural Bangladesh) from the sample.

  2. 2.

    District level data were collected directly from the records of the District Fisheries Office (DFO) in Bangladesh. DFO is governed by the Ministry of Fisheries and Livestock, Government of the People’s Republic of Bangladesh.

  3. 3.

    Previous studies also used agricultural capital (Dillon et al. 2015) and number of district agriculture officers (Benfica and Kilic 2016) as instruments to control endogeneity of agriculture income. In our context, we used aquaculture capital and number of district fisheries officers to control for the endogeneity of aquaculture income.

  4. 4.

    It has been found that on average household sold almost 39% of their harvested fish while consuming 54% and using 7% for other purposes (authors’ calculation). However, considering the harvest value of each fish will allow us to capture the value of different fish species produced in the homestead pond and therefore, reduces the risk of over estimating the value of total fish production.

  5. 5.

    The FAO/INFOODS food composition table (FCT) (Shaheen et al. 2013) and FAO/INFOODS density database- 2012 (Charrondiere et al. 2012) has been used to convert food intake data into energy (kilocalories).

  6. 6.

    The FCS score determines households’ food consumptions status based on three thresholds, i.e. poor with a score of 0 to 21, borderline with 21.5 to 35 and acceptable food consumption with a score above 35. A score of less than 35 is classified as inadequate consumption by WFP. However, the alternate cut-offs of 28 and 42 are more appropriate for poor and borderline category for populations with high frequency of consumption of sugar and oil. The maximum value of FCS can be 112, if the households consumed all food groups in each day.

  7. 7.

    The Simpson-Index used in this study is popularly known as the Berry-Index. This index was applied mainly in economic food diversity studies (Stewart and Harris 2005; Katanoda et al. 2006). Recently, it has been applied in nutritional studies to measure dietary diversity and its annual changes in different countries (Drescher et al. 2007).

  8. 8.

    Aquaculture systems were defined based on distinct production technology, which is a combination of characteristics, including the intensity of production, the type of waterbody in which production took place, the combination of species stocked, the management practices, the market orientation of production, and whether or not production was integrated with agriculture (Jahan et al. 2015).

  9. 9.

    Geographical hubs are the aquaculture clusters in Bangladesh that consist of groups of districts with similar agroecology. The main technologies practised in each hub were identified through a process of rapid appraisal with local key informants.

  10. 10.

    We prepared a two-year panel dataset collected from households that engaged in homestead pond aquaculture in Bangladesh. The first round of data was collected in 2011 for a CSISA-BD project while the second round was collected in 2016 only for this study using the same sampling procedures. For this study we could not use the data from 2011 since it did not collect information on household consumption expenditure.

  11. 11.

    The international threshold of 2122 kcal (kcal/capita/day) is recommended by the UN Food and Agricultural Organization (FAO) for the South Asian region.

  12. 12.

    Own calculation based on survey data 2016.

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Acknowledgements

We thank the Federal Ministry for Economic Cooperation and Development (BMZ), Germany for providing the financial support for this study under the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) project from 2014 to 2017. We would also like to specially thank Dr. Michael Phillips (Director, Aquaculture and Fisheries Science), Dr. Sven Genschick (Postdoc Fellow) from WorldFish Centre, Penang, Malaysia and Dr. Priyanka Parvathi (Postdoc Fellow) from the Institute of Development and Agricultural Economics, Hannover, Germany for their constructive comments on an earlier draft. We also thank Dr. K. A. Sayeed Murshid (Director General), Bangladesh Institute of Development Studies, Dhaka, Bangladesh for logistic support during the survey. Special thanks to all enumerators who helped us collect the data for the household survey.

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Ahmed, B.N., Waibel, H. The role of homestead fish ponds for household nutrition security in Bangladesh. Food Sec. 11, 835–854 (2019). https://doi.org/10.1007/s12571-019-00947-6

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Keywords

  • Aquaculture
  • Nutrition security
  • Agriculture household model
  • Two stages least squares
  • Simultaneous equations model
  • Developing country