The number of people worldwide living with dementia and cognitive impairment is increasing, mainly due to people living longer, so we want to figure out how where we live affects dementia and brain health as we get older. Some research suggests that where we live might influence our brain health. For example, poor air quality in towns and cities, can lead to a decline in brain health. As more of us now live in towns and cities, it is important that the environment where we live is scientifically designed and improved to maximise our brain health. The complex social and physical environments where we live make some people more vulnerable than others to developing cognitive impairment. In other words, the factors that account for who is most likely to develop cognitive ill-health due to the environment has less to do with 'how' we live and more to do with 'where' we live. We do not know how these factors interact to make urban environments a problem for brain health, nor which are the best policies and interventions for promoting healthy ageing and brain health for our poorest communities. Our project will provide evidence for policies and practices that provide supportive urban environments to promote healthy ageing, including promoting brain health. This could include using creative urban designs to support people to adopt and maintain healthier lifestyles such as being more active. However, this needs a strong evidence base with expert community advocates who can articulate how supportive urban environments can improve brain health. Our research has the following steps: 1. First, with the help of stakeholders, including those from business, industry, and local government, and a review of existing research, we will represent the relationships between our biology, our lifestyles and our environment in a diagram illustrating how they likely interact to affect brain health, because visual thinking can help stakeholders better identify possible intervention sweet-spots to improve brain health. 2. By analysing data from over 8,000 older people in Northern Ireland, and linking this to information about where they live, such as the amount of air pollution, the toxins in soil, or how walkable their neighbourhoods are, we will explore how different environmental factors relate to brain health. 3. Next, we will collect new data on a subgroup of 1,000 older people including more in-depth measures of brain health and better measures of physical activity, using GPS devices worn around the waist that monitor our locations. This will allow us to explore how the urban environment influences our brain health. 4. Then, we will explore how aspects of our biology play a role in how the urban environment affects our brain health. 5. We will host workshops with local citizens to 'sense-check' our findings and co-develop promising prevention approaches. In these, we will explore the acceptability, affordability, feasibility and sustainability of new initiatives to improve the environmental influences on brain health. This might include, for example, policies on: expanding the car-free areas of the city to reduce air pollution; increasing the number of footpaths and cycle paths to encourage walking and cycling; improving public transport to reduce car use. As a result of our research we will produce: 1. A map of the system in which our genes, lifestyle behaviours and urban environments interact to affect brain health, to help guide stakeholders towards policies and programmes that can improve brain health. 2. An evidence base exploring how where we live affects our brain health. 3. A suite of potential policies and interventions to improve brain health and promote healthy ageing 'tested' (in terms of acceptability and feasibility) with older people, business, industry, policymakers and other stakeholders.

We know that many signals and functions in the body follow a set pattern that repeats everyday (called circadian rhythms). We also know that the timing of this pattern can have an effect on how well our bodies work - for example, shift workers who are active and eat at night when most people are asleep tend to have more health problems such as diabetes and heart disease. Research using mice shows that these repeating patterns depend on the timing of daily events, like sleep, eating and activity. It is important to study humans as well because mice differ from us both in their behaviour and their metabolism - for example, mice are naturally most active at night and at times when food is limited they become even more active, with the chemistry in mouse muscle responding differently to human muscle. Muscles are some of the most important body parts for metabolism and health as they use most of the sugar and fat that we eat and have the capacity to dramatically increase our metabolism by moving around (contracting) - and an active lifestyle help us stay healthy. To prepare for this project, we did a pilot study where we took small pieces of muscle from the thighs of human volunteers every few hours for an entire day and night. We discovered repeating patterns in human muscle, with genetic signals linked to sugar, fat and protein metabolism going up and down every 24 hours. We did this once with people eating in the normal way during the daytime and fasting while asleep at night but also did other studies where we fed people through a tube during sleep - by feeding continuously we removed the acute responses to mealtimes and so could see the underlying rhythms in metabolism, and how they were affected by nutrient availability. Now that we have seen these patterns in genetic signals, our proven method of collecting human muscle samples for 24 hours whilst feeding continuously (even at night) can be used to study whether those signals actually change how our muscles use carbohydrate and protein over time. We will also be able to find out whether these rhythms in metabolism depend of whether and when the muscle contracts (by asking people to move around at different times of day). To study cause and effect we will use an experiment where volunteers are randomly divided into three groups: one group will rest for 24 hours, one group will be more active in the morning and the final group will be more active in the evening. We will then be able to see the pattern of metabolism in human muscle for the first time and can compare the muscle samples between the groups to learn about how rhythms in chemical processes are affected by muscle contraction. As an extra follow-up question, the volunteers will also then continue with their prescribed pattern of rest and activity for two weeks as part of their normal lives, just so we can explore how their muscles and health change in that time. Our prediction is that there will be clear 24-h rhythms in muscle metabolism, with more carbohydrate and protein taken into muscle to be used or stored earlier in the day. We also think that muscle contractions in the morning will be especially important in driving these rhythmic differences in metabolism over the course of a day. This research will provide the first information about changes in how our muscles use carbohydrate and protein over time and in relation to our activity patterns. This will improve understanding of how and why daily patterns as sleep, activity, diet and medications can be used to improve human health.