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| Name | Class |
|---|---|
| Ministry of Health, Singapore | OTHER_GOV |
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The aim of this study is to advance understanding of behavioural risk factors for cardiovascular disease and type 2 diabetes in Singapore.
BACKGROUND: Modifiable risk factors for non-communicable diseases, including unhealthy diets and movement behaviours, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real-life is essential to enable the design of precision public health interventions.
AIMS: The aims of this study are to (1) examine patterns of dietary and movement behaviours in real-time as people go about their daily lives, (2) examine how interactions with the social and physical environment influence dietary and movement behaviours, and (3) examine how these patterns differ by ethnicity and other socio-demographic characteristics.
METHOD: This is an observational study in free-living participants over 10 consecutive days, with a 9-day follow-up 6 months later. 1500 participants will be recruited from a large prospective cohort study. Real-time data capture strategies will be used: an ecological momentary assessment (EMA) app with global positioning system (GPS) enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA prompts per day to capture information on diet and movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. A second wave of EMA prompts and GPS monitoring will occur 6 months later. Data will be integrated and analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants.
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| Measure | Description | Time Frame |
|---|---|---|
| Movement behaviours | Movement behaviours (i.e., physical activity, sedentary behaviour, sleep) are measured using a wrist-worn accelerometer. | continuously for 9 days. |
| Glucose concentrations | Glucose concentrations are measured using a continuous glucose monitor sensor. | in 15-minute intervals over 9 days. |
| Self-reported food intake | Self-reported food intake measurement through entering of food items and the social and physical environment of eating via an Ecological Momentary Assessment (EMA) smartphone app. | Change in self-reported food intake over time. Data will be collected at 2.5-hour intervals between 8am and 9.30pm over a period of 9 days, and repeated at the 6-month follow-up |
| Self-reported movement behaviours | Self-reported movement behaviours (i.e., physical activity, sedentary behaviour, sleep) through entering of the type and social and physical environment context of activity via an Ecological Momentary Assessment (EMA) smartphone app. | Change in self-reported movement behaviours over time. Data will be collected at 2.5-hour intervals between 8am and 9.30pm over a period of 9 days, and repeated at the 6-month follow-up |
| Self-reported screen time | Self-reported screen time through entering of the type of screen used and the purpose and the duration of screen time via an Ecological Momentary Assessment (EMA) smartphone app. | Change in self-reported screen time over time. Data will be collected at 2.5-hour intervals between 8am and 9.30pm over a period of 9 days, and repeated at the 6-month follow-up |
| Measure | Description | Time Frame |
|---|---|---|
| Self-reported stress levels | Self-reported stress level will be assessed via an Ecological Momentary Assessment (EMA) smartphone app. | Data will be collected 6 times per day for 9 days, and repeated at the 6-month follow-up. |
| Self-reported fatigue |
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Inclusion criteria:
Exclusion criteria:
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Adults in Singapore
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| Name | Affiliation | Role |
|---|---|---|
| Rob M van Dam, PhD | National University of Singapore | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Saw Swee Hock School of Public Health, National University of Singapore | Singapore | 117549 | Singapore |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 35795338 | Background | Edney SM, Park SH, Tan L, Chua XH, Dickens BSL, Rebello SA, Petrunoff N, Muller AM, Tan CS, Muller-Riemenschneider F, van Dam RM. Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). Digit Health. 2022 Jun 30;8:20552076221110534. doi: 10.1177/20552076221110534. eCollection 2022 Jan-Dec. |
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| ID | Term |
|---|---|
| D015438 | Health Behavior |
| D009043 | Motor Activity |
| D057185 | Sedentary Behavior |
| D005247 | Feeding Behavior |
| ID | Term |
|---|---|
| D001519 | Behavior |
| D001522 | Behavior, Animal |
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Self-reported fatigue will be assessed via an Ecological Momentary Assessment (EMA) smartphone app.
| Data will be collected 6 times per day for 9 days, and repeated at the 6-month follow-up. |
| Self-reported positive affect | Self-reported positive affect will be assessed via an Ecological Momentary Assessment (EMA) smartphone app. | Data will be collected 6 times per day for 9 days, and repeated at the 6-month follow-up. |
| Self-reported hunger | Self-reported hunger will be assessed via an Ecological Momentary Assessment (EMA) smartphone app. | Data will be collected 6 times per day for 9 days, and repeated at the 6-month follow-up. |