Evidence map›Paper›PMID 32664897›Full record

ArticleBMC pulmonary medicine2020

Socio-economic Correlates and Spatial Heterogeneity in the Prevalence of Asthma among Young Women in India.

Shri Kant Singh, Jitendra Gupta, Himani Sharma, Sarang P Pedgaonkar, Nidhi Gupta

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Article in BMC pulmonary medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 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

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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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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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

5 authors.

Shri Kant SinghDepartment of Mathematical Demography & Statistics, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.
Jitendra GuptaDepartment of Mathematical Demography & Statistics, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India. jiitend@gmail.com.ORCID http://orcid.org/0000-0002-2658-3131
Himani SharmaDepartment of Mathematical Demography & Statistics, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.
Sarang P PedgaonkarDepartment of Population Policies & Programmes, International Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.
Nidhi GuptaInternational Institute for Population Sciences, Govandi Station Road, Deonar, Mumbai, 400088, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAsthma is one of the leading causes of disease burden when measured in terms of disability adjusted life years, despite low prevalence of self-reported cases among young women. This paper deals with the meso-scale correlates and spatial heterogeneity in the prevalence of self-reported Asthma across 640 districts in India, using a nationally representative sample of 699,686 women aged 15-49 years from all 36 States/UTs under NFHS-4 (2015-16).

methodsAnalytical methods used in this paper include multivariate logistic regression to examine the adjusted effects of various independent variables on self-reported Asthma and poor-rich ratios (PRR) and concentration index (CI) to understand the economic inequalities in the prevalence of Asthma. For the spatial analysis in the prevalence of Asthma, univariate and bivariate local Moran's I statistic have been computed in addition to measure of spatial autocorrelation and auto regression using spatial error and spatial lag models.

resultsResults highlight that women's education was an important marker to the prevalence of Asthma. Smoking tobacco in any form among women were significantly more likely to suffer from Asthma. The prevalence of Asthma was further aggravated among women from the households without a separate room for kitchen, as well as those using unclean fuel for cooking. The poor-rich ratio in the prevalence of Asthma across various States/UTs in India depict inherent inequality. An analysis of spatial clustering in the prevalence of Asthma based on spatial autocorrelation portrays that Moran's I values were significant for improved source of drinking water, clean fuel used for cooking, and household environment. When spatial weights are taken into consideration, the autoregression model noticeably becomes stronger in predicting the prevalence of Asthma.

conclusionsAny programmatic effort to curb the prevalence of Asthma through vertical interventions may hinge around the use of clean fuel, poverty, and lifestyle of subjects, irrespective of urban-rural place of their residence, environmental and ecological factors.

Indexed as

Socioeconomic FactorsSpatial AnalysisAdolescentAdultAsthmaCookingFamily CharacteristicsFemaleHumansIndiaLogistic ModelsMiddle AgedPrevalenceRisk FactorsRural PopulationSelf Reportand autoregressionAsthmaEnvironmental & Ecological FactorsLifestyleMoran’s ISpatial autocorrelationTobacco use

Identifiers

PMID32664897
PMCPMC7362630

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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.