The World Health Organization reports that up to five million deaths a year could be averted if the global population was more active and less sedentary, and describes these two behaviours as key to healthy ageing. Increases in physical activity and reductions in sedentary time are associated with reduced incidence of a number of age-related conditions such as cardiovascular disease, type 2 diabetes, and cancers. Despite the benefits of activity and low sedentary time, older adults are not meeting current ecommendations. Although interventions have been developed to reduce sedentary time and increase physical activity, sustained changes have not been achieved in older adults. Older adults have demonstrated the capacity to change in trial settings over the short-term. Therefore, they have the ability to choose to modify their activity levels (autonomy), can be motivated and are capable of succeeding in change (agency). However, it is also clear that there are barriers to longer term change that we need to overcome.

There are three key gaps in our understanding of the role that physical activity and sedentary time play in the health of older adults. Firstly, few studies have examined the prospective associations of physical activity and sedentary time with muscle mass indices, physical function and quality of life - three key components of healthy ageing. Importantly, the epidemiological literature thus far has largely relied on cross-sectional data, self-report measures of activity, has neglected to examine the whole spectrum of activity intensities (e.g. sedentary time and LPA) and has neglected older adults.

Secondly, there are few data on the correlates of changes in sedentary time, which could contribute to greater specificity in intervention development and delivery, including characterising context-specific behaviours which could be targeted by future interventions. Thirdly, given the nature of the problem, scalable digital interventions are likely to be required, but the limited evidence on the effectiveness of mobile app interventions in facilitating physical behaviour change has not been synthesised. Given smartphone use is already relatively common and increasing among older adult and apps have large potential reach over traditional health professional-delivered interventions, a population-based approach that includes apps to initiate small changes at the individual level may be cost-effective to achieve population impact. Addressing these gaps in knowledge will help inform the development of more effective intervention strategies.

I conducted five complementary studies to address these key gaps and to inform the development and evaluation of future interventions among older adults. In these five studies, I (i) quantified the bidirectional associations of change in sedentary time and physical activity with lean muscle mass indices (Study 1), physical function (Study 2) and health-related quality of life (Study 3) in older adults; (ii) described correlates of changes in sedentary time among older adults (Study 4); and (iii) conducted a systematic review and metaanalysis of trials of the effects of mobile app interventions on sedentary time, physical activity, and fitness among older adults (Study 5).

In the first four studies, I examined these associations in participants from the population-based EPIC Norfolk cohort study. Physical activity and sedentary time were assessed using accelerometers. Physical function measures included hand grip strength, usual walking speed and chair stand speed. Health-related quality-oflife (Hr-QoL) was measured using EuroQol-5D (EQ-5D) questionnaires, and muscle mass indices using DEXA (dual energy X-ray absorptiometry). Demographic factors assessed included sex, age, employment status, educational level, smoking status, BMI, occupational classification, and urban-rural status; behavioural factors included housework, gardening, cycling, walking, dog walking, TV/video viewing, computer use, newspaper reading, book reading, radio listening, and transport mode. In Study 5, I systematically searched five electronic databases for trials investigating effects of mobile health app interventions on sedentary time, physical activity and fitness among community-dwelling older adults. I calculated pooled standardised mean differences in these outcomes between intervention and control groups after the intervention period.

Broadly, I found positive bidirectional associations of physical activities with physical function, Hr-QoL and muscle mass indices and negative bidirectional associations of sedentary time variables with physical function, Hr-QoL and muscle mass indices. I also found that individuals in specific sub-groups (older, male, higher BMI) and who differentially participate in certain behaviours (less gardening, less walking and more television viewing) increased their sedentary time at a higher rate than others. Finally, I report that mobile health app interventions may be associated with reductions in sedentary time, increases in physical activity, and increases in fitness in trials ≤3 months and with increases in physical activity in trials ≥6 months. I conclude here that (i) light physical activity, total sedentary time and prolonged sedentary bout time ought to be considered as target behaviours to change, (ii) certain context-specific activities might be more effective in eliciting change, (iii) app-based interventions should be explored in older adults as our study highlights their potential efficacy but a lack of large RCTs (iv) particular behavioural change techniques (BCTs) appear to be more effective in app-based interventions and therefore should be considered for inclusion in future interventions (v) motivational messaging about muscle mass/physical function/Hr-QoL benefit should be considered for inclusions (vi) muscle mass, physical function and Hr-QoL indices should be included as secondary outcomes in future RCTs and cost effectiveness analyses so we do not underestimate intervention value.

Altogether, this thesis presents a more complete picture of physical behaviours in terms of correlates, important outcomes and emerging technologies. Taken together, these studies strengthen the case for physical behaviour interventions and highlight important information which needs to be considered early in future intervention design.