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
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File: /var/www/html/application/helpers/my_audit_helper.php
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Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: simplexml_load_file_from_url
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Function: getPubMedXML
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Function: GetPubMedArticleOutput_2016
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Function: pubMedSearch_Global
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Function: pubMedGetRelatedKeyword
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Function: require_once
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Introduction: Military service can significantly impact human health, with research showing that veterans experience higher mortality rates than the general population. However, limited data exist on the relationships of veteran status with biomarkers of aging that may precede clinical illness and mortality.
Methods: Using survey-design weighted generalized linear regression models, we examined the cross-sectional relationship of self-reported veteran status with DNA methylation (DNAm)-based biomarkers of aging (epigenetic age) in a representative sample of 2344 U.S. adults participating in the 1999-2000 and 2001-2002 cycles of the National Health and Nutrition Examination Survey. We tested 7 epigenetic aging markers: HannumAge, HorvathAge, SkinBloodAge, PhenoAge, GrimAge2, DNAm Telomere Length (TL), and DunedinPoAm.
Results: After adjusting for basic demographics, veterans had marginally greater SkinBloodAge (β = 0.86 years, 95% CI: -0.10, 1.81, P = .08) and GrimAge2 (β = 0.71 years, 95% CI: -0.07, 1.49, P = .07) measures when compared to nonveterans. Similar SkinBloodAge (β = 1.00 years, 95% CI: -0.01, 2.00, P = .05) and GrimAge2 (β = 0.69 years, 95% CI: -0.14, 1.52, P = .09) relationships were observed in fully-adjusted models where missing health and lifestyle covariates were imputed. Compared to nonveterans, veterans also had higher DNAm-estimated blood levels of GrimAge2-components hemoglobin A1c (β = 0.006, 95% CI: 0.0005, 0.01, P = .03) and protein TIMP1 (β = 71.14, 95% CI: 8.28, 134.01, P = .03) in basic demographic-adjusted models. In fully-adjusted imputed models (β = 96.40, 95% CI: -15.05, 207.85, P = .08) and complete case models (β = 98.66, 95% CI: -25.24, 222.55, P = .099), the TIMP1 relationships remained marginally significant.
Conclusions: Our marginal results support existing veteran morbidity and mortality literature while suggesting a modest utility of epigenetic aging biomarkers for further understanding veteran health. As veterans represent an important subset of the population and are a priority in federal government budgets, future research in this area holds the potential for significant public health and policy impact.
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http://dx.doi.org/10.1093/milmed/usaf071 | DOI Listing |