Evidence map›Paper›PMID 32912223›Full record

ArticleBMC public health2020

Considerations for the design of nutrition-sensitive production programmes in rural South Africa.

S L Hendriks, A Viljoen, D Marais, F A M Wenhold, A M McIntyre, M S Ngidi, J G Annandale, M Kalaba, D Stewart

Abstract read
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
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  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

S L HendriksDepartment of Agricultural Economics, Extension and Rural Development, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa. Sheryl.hendriks@up.ac.za.ORCID http://orcid.org/0000-0002-1487-4302
A ViljoenDepartment of Consumer Science, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa.
D MaraisDepartment of Plant and Soil Sciences, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa.
F A M WenholdDepartment of Human Nutrition, University of Pretoria, X323, Arcadia, Pretoria, 0007, South Africa.
A M McIntyreDepartment of Agricultural Economics, Extension and Rural Development, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa.
M S NgidiDepartment of Agricultural Extension and Rural Resource Management, School of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal, Pietermaritzburg, PBag01, Scottsville, 3209, South Africa.
J G AnnandaleDepartment of Plant and Soil Sciences, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa.
M KalabaDepartment of Agricultural Economics, Extension and Rural Development, University of Pretoria, PBag X01, Hatfield, Pretoria, 0028, South Africa.
D StewartLima Rural Development Foundation, 2 Forrester's Lane, Pietermaritzburg, 3201, South Africa.

Funding

South African National Research Foundation CRP20110706000020, 77053 and 80529South African Water Research Commission Project K5/2172/4
6 · The paper itself

Abstract

backgroundVery little has been researched about the efficacy, effectiveness, feasibility, sustainability and impact of food-based approaches on the diets and nutritional status of populations at risk of hunger and food insecurity. This study contributes knowledge about the impact of food-based approaches on the diets of populations at risk of hunger and food insecurity in four of the poorest rural communities in South Africa. The study investigated the consumption and production patterns of rural households (278 in summer and 280 in winter) in four sites in the poorest municipalities in South Africa.

methodsA multistage stratified random sampling technique was applied to identify the communities and sample households for the quantitative survey and qualitative assessments. Qualitative and quantitative data were collected between 2013 and 2015 through focus group discussions (FGDs), key informant interviews and the two-round panel survey to cover both the summer and winter seasons at each site.

resultsHome gardening led to a significant positive increase in the consumption of white roots and tubers, dark green leafy vegetables, orange-coloured fruit and other fruit in the 24 h prior to the survey. Participation in a community garden led to significant increases in the consumption of dark green leafy vegetables and other vegetables. School gardening did not demonstrate any statistical relationships with the consumption of foods from the crop-related food groups. Crop production improved dietary diversity. Selling produce and irrigation showed a stronger improvement in dietary diversity. Seasonality affected the availability of fresh fruit and vegetables for home consumption in winter.

conclusionsProducing beyond that solely for home consumption has greater benefits for dietary diversity and a consumption-smoothing effect during the post-harvest period. Politicians and the scientific community should recognise the role that household and small-scale crop production plays in supporting household consumption and the provision of essential micronutrients despite constraints and disincentives. Production and education programmes should focus on strengthening existing good consumption patterns and promoting the consumption of foods that can improve dietary diversity.

Indexed as

Nutritional StatusRural PopulationDietFood SupplyHumansSouth AfricaVegetablesAgricultural productionDietary diversityFood securityIrrigationNutrition-sensitive agriculture

Identifiers

PMID32912223
PMCPMC7488396

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.