About: The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China
Creator	Liu, Tao Jin, Dong-Hui Lv, Ling-Shuang Ma, Wen-Jun Xu, Yi-Qing Zhang, Xing-E Zhou, Chun-Liang
Source	PMC
abstract	The ambient temperature–health relationship is of growing interest as the climate changes. Previous studies have examined the association between ambient temperature and mortality or morbidity, however, there is little literature available on the ambient temperature effects on year of life lost (YLL). Thus, we aimed to quantify the YLL attributable to non-optimum ambient temperature. We obtained data from 1 January 2013 to 31 December 2017 of 70 counties in Hunan, China. In order to combine the effects of each county, we used YLL rate as a health outcome indicator. The YLL rate was equal to the total YLL divided by the population of each county, and multiplied by 100,000. We estimated the associations between ambient temperature and YLL with a distributed lag non-linear model (DNLM) in a single county, and then pooled them in a multivariate meta-regression. The daily mean YLL rates were 22.62 y/(p·100,000), 10.14 y/(p·100,000) and 2.33 y/(p·100,000) within the study period for non-accidental, cardiovascular, and respiratory disease death. Ambient temperature was responsible for advancing a substantial fraction of YLL, with attributable fractions of 10.73% (4.36–17.09%) and 16.44% (9.09–23.79%) for non-accidental and cardiovascular disease death, respectively. However, the ambient temperature effect was not significantly for respiratory disease death, corresponding to 5.47% (−2.65–13.60%). Most of the YLL burden was caused by a cold temperature than the optimum temperature, with an overall estimate of 10.27% (4.52–16.03%) and 15.94% (8.82–23.05%) for non-accidental and cardiovascular disease death, respectively. Cold and heat temperature-related YLLs were higher in the elderly and females than the young and males. Extreme cold temperature had an effect on all age groups in different kinds of disease-caused death. This study highlights that general preventative measures could be important for moderate temperatures, whereas quick and effective measures should be provided for extreme temperatures.
has issue date	2020-04-14(xsd:dateTime)
bibo:doi	10.3390/ijerph17082699
bibo:pmid	32295256
has license	cc-by
sha1sum (hex)	15017f9cd7f0f4c1ba6e14f0863757e0d4b9a591
schema:url	https://doi.org/10.3390/ijerph17082699
resource representing a document's title	The Impact of Non-optimum Ambient Temperature on Years of Life Lost: A Multi-county Observational Study in Hunan, China
has PubMed Central identifier	PMC7215980
has PubMed identifier	32295256
schema:publication	Int J Environ Res Public Health
resource representing a document's body	covid:15017f9cd7f0f4c1ba6e14f0863757e0d4b9a591#body_text
is schema:about of	named entity 'temperatures' named entity 'effective' named entity 'substantial' named entity 'This' named entity 'literature' named entity 'China' named entity 'extreme' named entity 'highlights' named entity 'single' named entity 'population' named entity 'LAG' named entity 'OBTAINED' named entity 'DECEMBER' named entity 'POPULATION' named entity 'ASSOCIATION' named entity 'YLL' named entity 'COUNTIES' named entity 'EFFECTIVE' named entity 'RELATED' named entity 'MALES' named entity 'INTEREST' named entity 'Thus' named entity 'higher' named entity 'cardiovascular disease' named entity 'respiratory disease' named entity '2013' named entity 'Hunan' named entity 'distributed lag' named entity 'Hunan' named entity '10.14' named entity 'data analysis' named entity 'confidence intervals' named entity 'human health' named entity 'ICD-10' named entity 'AIC' named entity 'cardiovascular' named entity 'black lines' named entity 'missing data' named entity 'global temperature' named entity 'demographic characteristics' named entity 'meteorological station' named entity 'Cardiovascular mortality' named entity 'China' named entity 'respiratory disease' named entity 'New Zealand' named entity 'socioeconomic status' named entity 'life table' named entity 'relative humidity' named entity 'cardiovascular disease' named entity '0.01' named entity 'cardiovascular diseases' named entity 'Hunan' named entity 'elderly people' named entity 'spline interpolation' named entity 'harmful effects' named entity 'respiratory disease' named entity '3, 4' named entity 'chronic diseases' named entity 'Intergovernmental Panel on Climate Change' named entity 'Hunan province' named entity 'cold days' named entity 'life table' named entity 'respiratory disease' named entity 'regression coefficient' named entity 'attributable risk' named entity 'China' named entity 'summary statistics' named entity 'China' named entity 'harvesting effect' named entity '10.14' named entity 'cholesterol' named entity '11.1' named entity 'respiratory disease' named entity 'burden of disease' named entity 'China'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software