Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach.
European Union
electricity
epidemiology
fixed effects model
heating and cooling
panel regression
prevalence
public health
random effects model
renewable energy
transport
Journal
International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455
Informations de publication
Date de publication:
18 06 2021
18 06 2021
Historique:
received:
30
04
2021
revised:
12
06
2021
accepted:
16
06
2021
entrez:
2
7
2021
pubmed:
3
7
2021
medline:
22
7
2021
Statut:
epublish
Résumé
The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.
Identifiants
pubmed: 34207010
pii: ijerph18126548
doi: 10.3390/ijerph18126548
pmc: PMC8296392
pii:
doi:
Substances chimiques
Carbon Dioxide
142M471B3J
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Références
Lancet. 2006 Mar 11;367(9513):859-69
pubmed: 16530580
Int J Environ Res Public Health. 2019 Aug 24;16(17):
pubmed: 31450595
Bull Environ Contam Toxicol. 2021 Jan;106(1):225-234
pubmed: 33462648
Health Econ Rev. 2017 Dec;7(1):7
pubmed: 28150127
Int J Environ Res Public Health. 2020 Sep 22;17(18):
pubmed: 32971840
J Environ Manage. 2021 Jan 15;278(Pt 2):111483
pubmed: 33129027
Environ Sci Pollut Res Int. 2021 Mar;28(10):12686-12698
pubmed: 33085009
Environ Sci Pollut Res Int. 2016 Aug;23(16):16699-715
pubmed: 27180840
Health Econ Rev. 2018 Aug 22;8(1):16
pubmed: 30136004
Int J Environ Res Public Health. 2020 Feb 18;17(4):
pubmed: 32085501