Associations between differential aging and lifestyle, environment, current, and future health conditions: Findings from Canadian Longitudinal Study on Aging

An aging population is a pressing challenge for the healthcare system. Insights into promoting healthy longevity can be gained by quantifying the biological aging process and understanding the roles of modifiable lifestyle and environmental factors and chronic disease conditions.We developed a biological age (BioAge) index by applying multiple state-of-art machine learning models based on easily accessible blood test data from the Canadian Longitudinal Study of Aging (CLSA). The BioAge gap, which is the difference between BioAge index and chronological age, was used to quantify the differential aging, i.e., the difference between biological and chronological age, of the CLSA participants. We further investigated the associations between the BioAge gap and lifestyle, environmental factors, and current and future health conditions.BioAge gap had strong associations with existing adverse health conditions (e.g., cancers, cardiovascular diseases, diabetes, kidney diseases) and future disease onset (e.g., Parkinson's disease, diabetes, and kidney diseases). We identified that frequent consumption of processed meat, pork, beef, and chicken, poor outcomes in nutritional risk screening, cigarette smoking, exposure to passive smoking, are associated with positive BioAge gap ("older" than expected in BioAge index). We also identified several modifiable factors, including eating fruits, legumes, vegetables, related to negative BioAge gap ("younger" than expected in BioAge index).Our study shows that a BioAge index based on easily accessible blood tests has the potential to quantify the biological aging process that is associated with current and future adverse health events. The identified risk and protective factors for differential aging indicated by BioAge gap are informative for guiding policy making to promote healthy longevity.