There is growing appreciation for the greater connectedness between the body and the mind, underscoring the importance of physical health to psychological wellbeing. This is especially important for young adults, who show disproportionately lower levels of wellbeing as a population. Healthy lifestyles—encompassing behaviours such as getting higher quality sleep, being physically active, and making healthy dietary choices— have emerged as promising health behaviours associated with improved wellbeing, but research investigating them are often limited in one of four key ways: (i) only testing one behaviour in isolation and thus ignoring potential interactions between them; (ii) not disaggregating within-person and between-person effects; (iii) not examining how mental distress may moderate these associations and; (iv) not capitalizing on the potential for new technologies to supplement traditional self-report data. The aim of this thesis was to address each of these limitations and advance our understanding of whether health behaviours may be a worthwhile pursuit to improve wellbeing. This aim was achieved through a systematic literature review of the existing research, followed by four empirical studies of young adults aged 17-25 years old. Study 1 employed an archival cross-sectional dataset (1,066 participants) of the lifestyles of young adults and utilized linear regression to examine three health behaviours of sleep quality, physical activity, and diet as simultaneous predictors of wellbeing, alongside potential interactions among the health behaviours in predicting wellbeing. Study 2 utilized a novel daily diary dataset (227 participants) and employed multilevel modelling to examine the health behaviours as simultaneous predictors of same day wellbeing at the within-person level. Depression and anxiety (common mental illnesses for young adults) were examined as potential moderators of the health behaviour and wellbeing associations, while wearable sensor data from Fitbits were also used to model similar inferences to the self-report data. Study 3 repeated the multilevel modelling on a larger archival daily diary dataset (821 participants) before using lagged data to test if health behaviour engagement could predict changes in next day wellbeing. Finally, in order to help the nascent use of advanced technology to examine health behaviour engagement, Study 4 collected focus group data (21 participants) and employed qualitative content analysis to unearth strategies for encouraging young adults' participation in such research. 4 Overall, results typically supported sleep quality, physical activity and fruit and vegetable consumption as additive significant predictors of wellbeing, both at the between-person and within-person levels. Interactions between the health behaviours and moderation effects by depression and anxiety were inconsistent across studies, except for a consistent protective relationship between sleep quality and fruit and vegetable consumption on wellbeing and an antagonistic relationship between depressive symptoms and physical activity on wellbeing. The health behaviours remained significant predictors of next-day wellbeing, but the nature of the associations differed from their same-day counterparts. Wearable sensor data produced similar inferences for physical activity’s relationship with wellbeing but not for sleep quality; researchers may consider more advanced technology, utilising the qualitative insights from Study 4 to encourage participant uptake. In sum, this thesis utilised multiple statistical approaches to extract a great level of detail regarding how these health behaviours associated with wellbeing, both advancing the field’s understanding and reaffirming health behaviours as promising pathways to better overall wellbeing.