The Objective of this project is to:

1) Pool physical activity data (measured by accelerometry) and associated variables from 14 studies worldwide to create a large, diverse, and contextually rich database

2) Utilise the high level of statistical power to investigate predictors of physical activity and associations with health in a range of population sub-groups (e.g. gender, minorities, socioeconomic groups, urban/rural communities).

3) Use the cultural diversity of the data to generate new models of children's physical activity behaviour, within a 'socio-ecological' framework.

Specific research questions:

1. Levels and patterns of physical activity

a) What are the physical activity levels, patterns and characteristics of children from diverse social, cultural, ethnic and geographical backgrounds?

2. Predictors of physical activity

a) What are the social, cultural, ethnic and geographical predictors of physical activity?

b) What are the personal, social, cultural, ethnic and geographical predictors of different dimensions (e.g. light/moderate/vigorous activity, sustained bouts, sedentary time) and patterns (e.g. daily, weekly, seasonal, active travel, PE/sport) of physical activity?

3. Associations between physical activity and health outcomes

a) What are the dose-response relationships between physical activity levels and a range of health outcomes (e.g. obesity, CVD risk)

b) What are the dose-response relationships between differing dimensions & patterns of physical activity and a range of health outcomes (e.g. obesity, CVD risk)

c) How do these associations vary within age, gender, social, cultural, ethnic and geographical groups?

The pooled database

Datasets have been identified through personal contacts and scrutiny of published literature. Data sources comprise of 14 studies worldwide, including the European Youth Heart Study (EYHS), Personal

and Environmental Associations with Children's Health (PEACH) and Sport, Physical activity

and Eating behaviour: Environmental Determinants in Young people (project SPEEDY). The full age range of the children measured in the 14 studies encompasses the full childhood and adolescent period (4-18 years), with some measurements on young adults (18-21 years). We estimate that data are available on over 28,000 children. When repeat measures from the longitudinal studies are included, the potential total is above 35,000.

Measurement of physical activity:

We will pool raw physical activity data derived from the MTI Actigraph accelerometer, model WAM

7164 (Actigraph LLC, Pensacola, FL) and its various predecessor models, which generate comparable data.

Data pooling procedures:

We expect that although data collection procedures have been consistent across studies, data reduction procedures will have differed. We will therefore wish to obtain raw accelerometer data from each study and apply standard data reduction software. This will create a standardised set of physical activity variables across the full dataset. Data sets have been selected, which fulfil the following criteria:

1) Have used the MTI Actigraph, WAM or GT1M accelerometer.

2) Have obtained a minimum of 3 days of 600 minutes/day of valid recording

3) Can contribute other data, including demographic (e.g. age, gender, ethnicity, socioeconomic position), psychosocial (e.g. self efficacy), anthropometric (e.g. obesity), educational (e.g. school type, attainment), physiological (e.g. fitness), health risk factors (e.g. obesity CVD risk factors), and environmental (e.g. urban/rural, travel to school, local amenities).

All variables will be renamed and re-labelled. Differences in coding structures will be investigated and re-coding performed where appropriate. A technical manual will be created fully describing all variables.

Specific ALSPAC requirements:

From ALSPAC we are requesting raw Actigraph DAT files from Focus 11+, TF2 and TF3, and corresponding anthropometric, fitness, body composition, psychosocial, socio-demographic and enviromental variables for these testing occasions. Limited parental and birth variables will also be requested.