Evidence map›Paper›PMID 34658488›Full record

ArticleWorld development2021

Gender and LPG use after government intervention in rural north India.

Sangita Vyas, Aashish Gupta, Nazar Khalid

Abstract read
In one paragraph

Article in World development, 2021. 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
–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

0 citing papers in PubMed.

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

3 authors.

Sangita VyasUniversity of Texas at Austin and r.i.c.e.
Aashish GuptaUniversity of Pennsylvania and r.i.c.e.
Nazar KhalidUniversity of Pennsylvania and r.i.c.e.

Funding

Population Research CenterR24HD042849 · NICHD · UNIVERSITY OF TEXAS AUSTIN · PI UMBERSON, DEBRA J. · 2002 to 2016
$8.4M
Training Program in Population StudiesT32HD007081 · NICHD · UNIVERSITY OF TEXAS AUSTIN · PI Aprile Dawn Benner, Abigail Mae Weitzman · 1985 to 2026
$6.8M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI MARK D. HAYWARD · 2017 to 2026
$5.2M
NICHD NIH HHS P2C HD042849NICHD NIH HHS R24 HD042849NICHD NIH HHS T32 HD007081
6 · The paper itself

Abstract

Exposure to air pollution from cooking with solid fuels has important consequences for public health. This paper focuses on rural north India, where despite robust economic growth and government subsidies, the vast majority of households mainly use solid fuels. We draw on new qualitative and quantitative data collected in the context of a policy environment that dramatically expanded ownership of liquid petroleum gas (LPG) to examine why households are slow to adopt clean fuels in rural north India. We find that patriarchal gender norms and attitudes encourage the use of solid fuels in this region. North Indian society confers low status to women, promotes women's seclusion, and constrains women's engagement in economic activities outside of the home. These beliefs encourage women to preserve gas, promote women's work that facilitates the use of solid fuels, and hinder communication between the cook and the decision-maker regarding LPG refills. When rural north Indian households use gas, it is frequently to facilitate the adherence to norms of seclusion that prevent women from leaving the home to collect solid fuels. In addition to expanding access and improving economic conditions, future research and policy interventions should pay careful attention to the gender norms and attitudes that discourage the use of gas. Addressing these beliefs and norms is essential to sustained LPG use and health improvements.

Indexed as

energy transitiongenderIndiaLPGsolid fuels

Identifiers

PMID34658488
PMCPMC8513635

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.