Objectively Determined Activity Patterns Among Youth Living in a Deprived Area in Copenhagen, Denmark: The WCMC Study

Background The local build environment is believed to play an important role in youth physical activity (PA) as their independent mobility is restricted. To be able to target interventions to promote PA among youth knowledge about objectively measured PA patterns is important. We would like to be able to answer questions like: When and where are youth active? How much does school day or leisure time contribute to overall PA? How much time is spent close to home? What are typical roaming distances?

Objectives The overall objective of the When Cities Move Children (WCMC) study is to determine the effects of urban renewal on PA level and activity patterns among youth (10-16yrs old) living in a deprived area with 40% having a multi-ethnic background, in Copenhagen, Denmark. The specific objective for this paper is to describe the PA pattern of the study participants at baseline.

Methods For our baseline study, carried out in spring 2010, 551 youth enrolled at three public schools in the study area were asked to wear an accelerometer (ActiGraph GT3X) and a GPS (Qstarz BT-Q1000X) for 7 days (5 week days, 2 weekend days) to determine their level of PA and movement patterns. Their GPS position was recorded every 15 seconds and their PA level was registered every 2 seconds. GPS and accelerometer data were compiled and joined using an internet based computer program, the Physical Activity Location Measurement System (PALMS), developed by the Center for Wireless & Population Health Systems at the University of California, San Diego.

Initial analyses of accelerometer data was conducted using the computer software Propero, developed by the University of Southern Denmark. Propero was used to compile accelerometer data on different day-parts and exported to STATA for further analyses. Data were examined for extreme accelerometer values (above 20.000 counts and negative values) and were aggregated to counts per minute (CPM).

The following minimum acceptance criteria were applied to determine which participants to include:

• A valid day consists of at least 8 hours wear time between 6am and midnight. Non-wear is defined as 60 or more minutes of consecutive zeros, allowing for two activity epochs in each block of non-wear.
• A valid week consists of at least 4 valid days, including at least 1 weekend day.
• A valid weekend consists of at least 1 valid weekend day.
• A valid school week consists of at least 3 valid week days.
• A valid morning consists of at least 30 minutes of wear time between 6am and 8:10am. Non-wear is defined as 10 or more minutes of consecutive zeros, allowing for 1 activity epoch in each block of nonwear.
• Valid school week mornings consist of at least 3 valid mornings.
• A valid school day consists of at least 3 hours of wear time between 8:10am and 1:30pm. Non-wear is defined as 60 or more minutes of consecutive zeros, allowing for 2 activity epochs in each block of nonwear.
• A valid school week consists of at least 3 valid school days.
• A valid leisure time school day consists of at least 4.5 hours of wear time between 1:30pm and midnight. Non-wear is defined as 60 or more minutes of consecutive zeros, allowing for 2 activity epochs in each block of non-wear.
• Valid school week leisure time consists of at least 3 valid leisure time days.

Results Accelerometer data were downloaded for 454 participants (82.4%). 271 participants had a valid week, 243 had a valid school week, 148 had valid school week mornings and 254 had valid school week leisure time. Average Mean CPM (MCPM) for a valid week is 484.2 (min 106.5, max 1367.6). MCPM for a school week is 501.4 (min 22.8, max 2407.6) and for weekends 439.0 (min 36.9, max 6062.8). MCPM during school week mornings is 673.0 (min 65.1, max 2169.4), school day average MCPM is 482.4 (min 137.4, max 1829.0), school week leisure time average MCPM is 488.8 (min 21.1, max 2199.7). Mean CPM during a school week is 14.2% higher than during weekends. MCPM during school week mornings is 34.2% higher than week day CPM, school day average MCPM is 3.8% lower than week day CPM and leisure time MCPM is 2.6% lower.

Conclusions Physical activity patterns among youth can be described according to how physical active they are during different parts of the day. However, low compliance to morning criteria presents a validity problem. Preliminary results show that youth are more active during the week compared to weekends. During school day activity levels are highest in the morning, presumable due to active transportation to school, while the least activity is seen in leisure time and in school hours.