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Characteristics of Households’ Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India
by
Dutta, Ambarish
, Nanda, Lipika
, Chakraborty, Soham
, Mishra, Saswat Kishore
, Rathi, Suresh Kumar
in
Cities
/ Cross-Sectional Studies
/ Extreme Heat - adverse effects
/ Family Characteristics
/ Fever
/ Forest & brush fires
/ Heat
/ Hot Temperature
/ Households
/ Humans
/ India - epidemiology
/ Mortality
/ Physiology
/ Population
/ Questionnaires
2022
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Characteristics of Households’ Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India
by
Dutta, Ambarish
, Nanda, Lipika
, Chakraborty, Soham
, Mishra, Saswat Kishore
, Rathi, Suresh Kumar
in
Cities
/ Cross-Sectional Studies
/ Extreme Heat - adverse effects
/ Family Characteristics
/ Fever
/ Forest & brush fires
/ Heat
/ Hot Temperature
/ Households
/ Humans
/ India - epidemiology
/ Mortality
/ Physiology
/ Population
/ Questionnaires
2022
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Do you wish to request the book?
Characteristics of Households’ Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India
by
Dutta, Ambarish
, Nanda, Lipika
, Chakraborty, Soham
, Mishra, Saswat Kishore
, Rathi, Suresh Kumar
in
Cities
/ Cross-Sectional Studies
/ Extreme Heat - adverse effects
/ Family Characteristics
/ Fever
/ Forest & brush fires
/ Heat
/ Hot Temperature
/ Households
/ Humans
/ India - epidemiology
/ Mortality
/ Physiology
/ Population
/ Questionnaires
2022
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Characteristics of Households’ Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India
Journal Article
Characteristics of Households’ Vulnerability to Extreme Heat: An Analytical Cross-Sectional Study from India
2022
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Overview
High ambient temperature is a key public health problem, as it is linked to high heat-related morbidity and mortality. We intended to recognize the characteristics connected to heat vulnerability and the coping practices among Indian urbanites of Angul and Kolkata. In 2020, a cross-sectional design was applied to 500 households (HHs) each in Angul and Kolkata. Information was gathered on various characteristics including sociodemographics, household, exposure, sensitivity, and coping practices regarding heat and summer heat illness history, and these characteristics led to the computation of a heat vulnerability index (HVI). Bivariate and multivariable logistic regression analyses were used with HVI as the outcome variable to identify the determinants of high vulnerability to heat. The results show that some common and some different factors are responsible for determining the heat vulnerability of a household across different cities. For Angul, the factors that influence vulnerability are a greater number of rooms in houses, the use of cooling methods such as air conditioning, having comorbid conditions, the gender of the household head, and distance from nearby a primary health centre (PHC). For Kolkata, the factors are unemployment, income, the number of rooms, sleeping patterns, avoidance of nonvegetarian food, sources of water, comorbidities, and distance from a PHC. The study shows that every city has a different set of variables that influences vulnerability, and each factor should be considered in design plans to mitigate vulnerability to extreme heat.
Publisher
MDPI AG,MDPI
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