Analysing the potential impacts of three interventions on fruit and vegetable consumption in urban Kenya using participatory systems modelling
Bibliographic Data
| ID | 15096462 |
|---|---|
| Authors | Charles F Nicholson (0000-0001-8245-8864, University of Wisconsin–Madison, corresponding author), Eva Monterrosa (0000-0003-1665-0756, Global Alliance for Improved Nutrition) |
| Year | 2023 |
| Volume | 26 |
| Issue | 12 |
| Pages | 3076-3087 |
| Publication date | 2023-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Health Nutrition (JOURNAL) |
| Journal identifiers | ISSN: 1368-9800 • E-ISSN: 1475-2727 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1368980023002033 |
| PMID | 37721018 |
| OpenAlex | W4386818058 |
| Language | EN |
| Citations received | 1 |
| References cited | 16 |
Objective: This study uses participatory modelling with stakeholders to assess the potential impacts of three interventions intended to increase fruit and vegetable (F&V) consumption in urban Kenya. Design: A participatory process using Group Model Building (GMB) developed a conceptual model of the determinants of vegetable consumption. A subsequent quantitative System Dynamics model using data from primary and secondary sources simulated vegetable consumption from 2020 to 2024 under three proposed interventions suggested by stakeholders: increasing consumer awareness, reducing post-harvest losses and increasing farm yields. Model analyses assumed mean parameter values and assessed uncertainty using 200 simulations with randomised parameter values. Setting: The research was implemented in Nairobi, Kenya with simulation analyses of mean per capita consumption in this location. Participants: Workshops convened diverse F&V value chain stakeholders (farmers, government officials, NGO staff and technical experts) to develop the conceptual model, data inputs and intervention scenarios. Results: Increasing consumer awareness was simulated to increase vegetable consumption by relatively modest amounts by 2024 (5 g/person/d from a base of 131 g/person/d) under mean assumed value of value chain response parameters. Reducing perishability was simulated to reduce consumption due to the higher costs required to reduce losses. Increasing farm yields was simulated to have the largest impact on consumption at assumed parameter values (about 40 g/person/d) but would have a negative impact on farm profits, which could undermine efforts to implement this intervention. Conclusions: The combination of GMB and simulation modelling informed intervention priorities for an important public health nutrition issue
Agricultural economics · Business · Citizen journalism · Consumption (sociology · Economics · Environmental economics · Environmental health · Per capita · Population · Psychological intervention · Sociology · Agricultural Innovations and Practices · Complex Systems and Decision Making · Computer Science · Medicine · Sustainable Agricultural Systems Analysis
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| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |