Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1057
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3175
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Aging is a driving factor of various non-communicable diseases. Air pollution and greenspace also affect human health to varying degrees. However, the relationship between air pollution, green space and aging has not been clearly studied. To address this gap, we conducted a study estimating the biological age of 156,690 individuals in the UK Biobank using the PhenoAge algorithm from clinical traits. We defined the residual between biological age and actual age as Phenotypic Age Acceleration (PhenoAgeAccel) to indicate the acceleration of biological aging. Our analysis utilized linear regression models to investigate the relationships between environmental exposures of air pollution/greenspace and PhenoAgeAccel. Stratification analyses were performed based on sex, smoking status, drinking status, body mass index and telomere length. Additionally, we explored potential interactions by setting variable cross-product terms of environment exposures with smoking and drinking status into the models. We observed that air pollution, such as PM (β = 0.151, P = 1.17 × 10) and PM (β = 0.041, P = 1.28 × 10), was positively correlated with PhenoAgeAccel, while green space was negatively correlated with PhenoAgeAccel, as seen with 1000 m buffer of green space (β = - 0.003, P = 2.28 × 10). Subgroup analysis indicated that non-smokers, former smokers, drinkers, obese and overweight individuals and female were more sensitive to air pollution and green space exposures. Furthermore, we identified interaction effects of alcohol intake and air pollution/greenspace that were associated with PhenoAgeAccel. Our results highlight the positive correlation between air pollution and biological aging, as well as the negative correlation between green space and biological aging.
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Source |
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http://dx.doi.org/10.1007/s11357-025-01597-7 | DOI Listing |
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