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al s work here reflects the researchers previous studies on how the advanced technology they use beats chronological age in predicting all-cause mortality3, and how it can generally track age-related alterations.4 Other researchers have found the effects of smoking on aging, including one study that used DNA methylation clocks,5 but this study is the first using a deep learning-based approach to measure tobacco use and aging

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Study selection and data extraction We included prospective cohorts with at least 50 cardiovascular disease events (mortality, morbidity, or both) to minimise the potential for reporting bias, in which large but unreliable effects might be seen in small studies