Evidence map›Paper›PMID 31446482›Full record

ArticleInternational journal of biometeorology2019

Appraisal of the heat vulnerability index in Punjab: a case study of spatial pattern for exposure, sensitivity, and adaptive capacity in megacity Lahore, Pakistan.

Syeda Samee Zuhra, Amtul Bari Tabinda, Abdullah Yasar

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Article in International journal of biometeorology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Syeda Samee ZuhraGovernment College University, Lahore, Pakistan. samienv.sc@gmail.com.
Amtul Bari TabindaGovernment College University, Lahore, Pakistan.
Abdullah YasarGovernment College University, Lahore, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, the heat vulnerability index has been developed for a megacity Lahore. Although Pakistan stands at 12th rank among highly exposed countries to climate change, very little research has been dedicated in exploring the heat-related vulnerability of exposed populations. We have applied the principal component analysis with varimax rotation on well-established indicators of exposure, sensitivity, and adaptive capacity to determine the heat vulnerability. This study has resulted in two principal components sharing 70.4% variance. Principal component 1 comprises pre-existing illness, population density, housing density, education, and normalized difference vegetation index with following significant (> 0.4) loading values 0.91, 0.91, 0.91, 0.57, and - 0.773, respectively, and principal component 2 combines the nature of housing material (0.964) followed by the water availability (0.962) and minority status (0.539). The hot spot analysis and overlay analysis have also been applied on the extracted component, and the resultant co-occurrence of high variable class, high vulnerability, and hot spots of vulnerability helped to grip those areas which imperatively require the applications of heat-related health interventions. The heat vulnerability index developed in our study clarifies that the most vulnerable populations are confined in the central vicinities of Lahore and less vulnerable are those which inhibit towards the outskirts of the city.

Indexed as

Climate ChangeHot TemperatureCitiesHumansPakistanVulnerable PopulationsAdaptive capacityHeat vulnerability indexOverlay analysisPrincipal component analysisSensitivity

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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.