Evidence map›Paper›PMID 31847831›Full record

ArticleBMC pregnancy and childbirth2019

Maternal BMI mediates the impact of crop-related agricultural work during pregnancy on infant length in rural Pakistan: a mediation analysis of cross-sectional data.

Rebecca Pradeilles, Elizabeth Allen, Haris Gazdar, Hussain Bux Mallah, Azmat Budhani, Rashid Mehmood, Sidra Mazhar, Ayesha Mysorewala, Saba Aslam, Alan D Dangour and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 40% of its field
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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 2 institutions in 1 country.

Rebecca PradeillesDepartment of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Elizabeth AllenDepartment of Medical Statistics, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Haris GazdarCollective for Social Science Research, Karachi, Pakistan.
Hussain Bux MallahCollective for Social Science Research, Karachi, Pakistan.
Azmat BudhaniCollective for Social Science Research, Karachi, Pakistan.
Rashid MehmoodCollective for Social Science Research, Karachi, Pakistan.
Sidra MazharCollective for Social Science Research, Karachi, Pakistan.
Ayesha MysorewalaCollective for Social Science Research, Karachi, Pakistan.
Saba AslamCollective for Social Science Research, Karachi, Pakistan.
Alan D DangourDepartment of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
Elaine FergusonDepartment of Population Health, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK. elaine.ferguson@lshtm.ac.uk.ORCID http://orcid.org/0000-0003-4673-5128
London School of Hygiene & Tropical Medicine · GBLoughborough University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStunted growth in early infancy is a public health problem in low-and-middle income countries. Evidence suggests heavy agricultural work during pregnancy is inversely associated with maternal body mass index (BMI) and infant birth weight in low- and middle-income countries; but pathways linking agricultural work to length-for-age Z-scores (LAZ) in early infancy have not been examined. This study aimed to investigate the relationship between agricultural work during pregnancy, post-natal maternal BMI and LAZ among young infants in rural Pakistan; and explored whether maternal BMI mediated the relationship between agricultural work and infant LAZ.

methodsA cross-sectional survey was conducted from December 2015 to January 2016 in rural Sindh, Pakistan. Mother-infant dyads were recruited via systematic random cluster sampling at 2-12 weeks' post-partum (n = 1161). Anthropometric measurements (maternal and infant height/length and weight) and questionnaire data were collected. Multivariable linear regression and structural-equation based mediation analyses were used to examine associations of agricultural work during pregnancy with maternal BMI and infant LAZ.

resultsDuring pregnancy, women reported engaging in livestock-related work (57.0%), crop-related work (42.7%), and cotton harvesting (28.4%). All three forms of agricultural work were negatively associated with maternal BMI (β = - 0.67 [- 1.06; - 0.28], β = - 0.97 [- 1.51; - 0.48]; and β = - 0.87 [- 1.33; - 0.45], respectively). Maternal engagement in cotton harvesting alone was negatively associated with infant LAZ after controlling for confounding factors. The total negative effect of cotton harvesting on infant LAZ was - 0.35 [- 0.53; - 0.16]. The indirect effect of maternal BMI on infant LAZ was - 0.06 [- 0.08; - 0.03], revealing that 16% (- 0.06/- 0.35) of the relationship between cotton harvesting and infant LAZ, after adjustment, was mediated via maternal BMI.

conclusionThese results underscore a need to reduce labour-intensive agricultural workload demands during pregnancy, especially in cotton harvesting, to reduce risks of negative maternal energy balance and poor growth outcomes in early infancy.

Indexed as

AgricultureBody Mass IndexAdultAnthropometryBirth WeightCluster AnalysisCrops, AgriculturalCross-Sectional StudiesFemaleGrowth DisordersHumansInfantInfant, NewbornMaleMaternal ExposureMothersAgricultural workInfantMediation analysisNutritional statusRural PakistanWomen

Identifiers

PMID31847831
PMCPMC6918638
OpenAlexW2994877899

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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.