Evidence map›Paper›PMID 34660880›Full record

ArticleSSM - population health2021

Spatial location, temperature and rainfall diversity affect the double burden of malnutrition among women in Kenya.

Japheth Muema Kasomo, Ezra Gayawan

Abstract read
In one paragraph

Article in SSM - population health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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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

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

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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

2 authors.

Japheth Muema KasomoAfrican Institute for Mathematical Sciences (AIMS), Plots # 559-560-561, Kicukiro District, Niboye Sector, Nyakabanda Cell, PO BOX: 7150, KG3 ST, Rwanda.
Ezra GayawanHead, Biostatistics and Spatial Modelling Research Laboratory, Department of Statistics, Federal University of Technology, Akure, PMB 704, Akure, Ondo State, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies have looked into how environmental and climate covariates affect under-and over-nutrition, but little is known about the spatial distribution of different forms of malnutrition in Kenya and whether there are locations that suffer from double-burden of malnutrition. This research quantifies spatial variations and estimates how climatic and environmental factors affect under-and over-nutrition among women in Kenya. This enables us to determine if the patterns in which these factors affect the malnutrition indicators are similar and whether there are overlaps in the spatial distributions. The study used data from the Demographic and Health Survey, which included cross-sectional data on malnutrition indicators as well as some climate and environmental variables. A multicategorical response variable that classified the women into one of four nutritional classes was generated from the body mass index (BMI) of the women, and a Bayesian geoadditive regression model with an estimate based on the Markov chain Monte Carlo simulation technique was adopted. Findings show that women in Turkana, Samburu, Isiolo, Baringo, Garissa, and West Pokot counties are more likely to be underweight than women in other counties while being overweight is prevalent in Kirinyag'a and Kitui counties. Obesity is prevalent in Kirinyag'a, Lamu, Kiambu, Murang'a, and Taita Taveta counties. The study further shows that as mean temperature and precipitation increase, the likelihood of being underweight reduces. The chances of being underweight are lower among literate women [OR: 0.614; 95% CrI: 0.513,0.739], married women [OR: 0.702; 95% CrI: 0.608,0.819] and those from rich households [OR: 0.617; 95% CrI: 0.489,0.772], which is not the case for overweight and obesity. The generated spatial maps identify hot spots of the double burden of malnutrition that can assist the government and donor agencies in channeling resources efficiently.

Indexed as

ClimateFood securityGeoadditive regression modelMalnutritionSpatial effects

Identifiers

PMID34660880
PMCPMC8503666

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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.