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Active (Opt-In) Consent Underestimates Mean BMI-z and the Prevalence of Overweight and Obesity Compared to Passive (Opt-Out) Consent. Evidence from the Healthy Together Victoria and Childhood Obesity Study

Author

Listed:
  • Claudia Strugnell

    (Global Obesity Centre, Centre for Population Health Research, Deakin University, 1 Gheringhap Street, Geelong, VIC 3220, Australia)

  • Liliana Orellana

    (Biostatistics Unit, Deakin University, Geelong, VIC 3220, Australia)

  • Joshua Hayward

    (Global Obesity Centre, Centre for Population Health Research, Deakin University, 1 Gheringhap Street, Geelong, VIC 3220, Australia)

  • Lynne Millar

    (Australian Health Policy Collaboration, Victoria University, Melbourne, VIC 8001, Australia
    Australian Institute of Musculoskeletal Science, The University of Melbourne and Western Health, St Albans, VIC 3021, Australia)

  • Boyd Swinburn

    (Global Obesity Centre, Centre for Population Health Research, Deakin University, 1 Gheringhap Street, Geelong, VIC 3220, Australia
    School of Population Health, University of Auckland, Auckland 1142, New Zealand)

  • Steven Allender

    (Global Obesity Centre, Centre for Population Health Research, Deakin University, 1 Gheringhap Street, Geelong, VIC 3220, Australia)

Abstract

Background: Tracking population trends in childhood obesity and identifying target areas for prevention requires accurate prevalence data. This study quantified the magnitude of non-participation bias for mean Body Mass Index-z scores and overweight/obesity prevalence associated with low (opt-in) compared to high (opt-out) participation consent methodologies. Methods: Data arose from all Local Government Areas (LGAs) participating in the Healthy Together Victoria Childhood Obesity Study, Australia. Primary schools were randomly selected in 2013 and 2014 and all Grades 4 and 6 students (aged approx. 9–12 years) were invited to participate via opt-in consent (2013) and opt-out consent (2014). For the opt-in wave N = 38 schools (recruitment rate (RR) 24.3%) and N = 856 students participated (RR 36.3%). For the opt-out wave N = 47 schools (RR 32%) and N = 2557 students participated (RR 86.4%). Outcomes: differences between opt-in and opt-out sample estimates (bias) for mean BMI-z, prevalence of overweight/obesity and obesity (alone). Standardized bias (Std bias) estimates defined as bias/standard error are reported for BMI-z. Results : The results demonstrate strong evidence of non-participation bias for mean BMI-z overall (Std bias = −4.5, p < 0.0001) and for girls (Std bias = −5.4, p < 0.0001), but not for boys (Std bias = −1.1, p = 0.15). The opt-in strategy underestimated the overall population prevalence of overweight/obesity and obesity by −5.4 and −4.5 percentage points respectively ( p < 0.001 for both). Significant underestimation was seen in girls, but not for boys. Conclusions: Opt-in consent underestimated prevalence of childhood obesity, particularly in girls. Prevalence, monitoring and community intervention studies on childhood obesity should move to opt-out consent processes for better scientific outcomes.

Suggested Citation

  • Claudia Strugnell & Liliana Orellana & Joshua Hayward & Lynne Millar & Boyd Swinburn & Steven Allender, 2018. "Active (Opt-In) Consent Underestimates Mean BMI-z and the Prevalence of Overweight and Obesity Compared to Passive (Opt-Out) Consent. Evidence from the Healthy Together Victoria and Childhood Obesity ," IJERPH, MDPI, vol. 15(4), pages 1-11, April.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:4:p:747-:d:140958
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    References listed on IDEAS

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    1. Jennifer M. Mellor & Ronald B. Rapoport & Daniel Maliniak, 2008. "The Impact of Child Obesity on Active Parental Consent in School-Based Survey Research on Healthy Eating and Physical Activity," Evaluation Review, , vol. 32(3), pages 298-312, June.
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