| Title |
Production diversification, dietary diversity and consumption seasonality: panel data evidence from Nigeria
|
|---|---|
| Published in |
BMC Public Health, August 2018
|
| DOI | 10.1186/s12889-018-5887-6 |
| Pubmed ID | |
| Authors |
Habtamu Yesigat Ayenew, Sibhatu Biadgilign, Lena Schickramm, Getachew Abate-Kassa, Johannes Sauer |
| Abstract |
Despite some improvements towards reducing hunger, malnutrition remains to be a crucial challenge in the developing world. The objective of this paper is to analyze the interplay between production diversity and dietary diversity across different seasons in rural Nigeria. The paper also investigates the relationship across different income quantiles. The study uses the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) dataset of the World Bank. We use two rounds of survey data (2010 and 2012) from Nigeria. Data were collected in two visits: at post-planting (from September to November), and at post-harvesting (from February to April). We analyze the relationship between production diversity and dietary diversity using different panel data regression tools. In post-harvest season, an increase in farm production diversification is associated with an increase with dietary diversity. On the other hand, production diversification does not have a significant contribution to the dietary diversity at post-planting. The analysis reveals that production diversification leads to better diet diversity for households in the second and third income quantiles. Seasonal variation on the contribution of production diversification on dietary diversity in rural Nigeria calls for the role of seasonally targeted policies. A higher propensity of households in the poorest quantile for malnutrition irrespective of the season suggests the need for targeted and continuous public health and nutrition interventions. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 147 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 147 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 21 | 14% |
| Researcher | 19 | 13% |
| Student > Ph. D. Student | 16 | 11% |
| Student > Doctoral Student | 10 | 7% |
| Student > Postgraduate | 8 | 5% |
| Other | 22 | 15% |
| Unknown | 51 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 15% |
| Economics, Econometrics and Finance | 16 | 11% |
| Nursing and Health Professions | 13 | 9% |
| Social Sciences | 12 | 8% |
| Medicine and Dentistry | 9 | 6% |
| Other | 18 | 12% |
| Unknown | 57 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 October 2019.
All research outputs
#1,967,924
of 23,099,576 outputs
Outputs from BMC Public Health
#2,170
of 15,063 outputs
Outputs of similar age
#42,841
of 331,157 outputs
Outputs of similar age from BMC Public Health
#56
of 295 outputs
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