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Updated: May 13, 2026
Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Predictors of non-response in a UK-wide cohort study of children's accelerometer-determined physical activity using
Carly Rich1, Mario Cortina-Borja, Carol Dezateux
1MRC Centre of Epidemiology for Child Health, UCL Institute of Child Health, London, UK.
Insights
Many factors influence participation in children's activity studies. Understanding these can improve data collection and reduce bias in research on child health.
Area of Science:
- Pediatric research
- Public health surveillance
- Biomedical data acquisition
Background:
- Accurate measurement of children's physical activity is crucial for understanding health.
- Postal-based studies offer a scalable method for large-scale data collection.
- Non-response bias can significantly impact the generalizability of findings.
Purpose of the Study:
- To identify factors associated with non-consent and non-return of accelerometer data in a UK-wide study.
- To inform strategies for improving participation and data quality in child activity research.
- To mitigate non-response bias in studies involving objective physical activity measurement.
Main Methods:
- Nationally representative prospective cohort study of UK children born 2000-2002.
- 13,681 children aged 7-8 years invited to wear an accelerometer for 7 days.
- Data collected via postal dispatch and return of Actigraph GT1M accelerometers.
Main Results:
- Consent rate was 94.5%, with reliable accelerometer data returned by 50.5% of consenting participants.
- Lower consent was associated with limiting illness, non-smoking households, garden access, and Northern Ireland residence.
- Factors reducing reliable data return included male sex, overweight/obesity, certain ethnicities, maternal education, living conditions, physical activity levels, breastfeeding, socioeconomic status, and household composition.
Conclusions:
- Targeted efforts are needed to enhance consent and reliable data return across diverse demographic and socioeconomic groups.
- Addressing identified barriers can improve study response rates and reduce non-response bias.
- Statistical adjustments for non-random missing data are essential for valid research conclusions.
Objectives:
To investigate the biological, social, behavioural and environmental factors associated with non-consent, and non-return of reliable accelerometer data (≥2 days lasting ≥10 h/day), in a UK-wide postal study of children's activity.
Design:
Nationally representative prospective cohort study.
Setting:
Children born across the UK, between 2000 and 2002.
Participants:
13 681 7 to 8-year-old singleton children who were invited to wear an accelerometer on their right hip for 7 consecutive days. Consenting families were posted an Actigraph GT1M accelerometer and asked to return it by post.
Primary Outcome Measures:
Study consent and reliable accelerometer data acquisition.
Results:
Consent was obtained for 12 872 (94.5%) interviewed singletons, of whom 6497 (50.5%) returned reliable accelerometer data. Consent was less likely for children with a limiting illness or disability, children who did not have people smoking near them, children who had access to a garden, and those who lived in Northern Ireland. From those who consented, reliable accelerometer data were less likely to be acquired from children who: were boys; overweight/obese; of white, mixed or 'other' ethnicity; had an illness or disability limiting daily activity; whose mothers did not have a degree; who lived in rented accommodation; who exercised once a week or less; who had been breastfed; were from disadvantaged wards; had younger mothers or lone mothers; or were from households with just one, or more than three children.
Conclusions:
Studies need to encourage consent and reliable data return in the wide range of groups we have identified to improve response and reduce non-response bias. Additional efforts targeted at such children should increase study consent and data acquisition while also reducing non-response bias. Adjustment must be made for missing data that account for missing data as a non-random event.
