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Identification of measurement needs to prevent childhood obesity in high-risk populations and environments
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11 2020
Source: Am J Prev Med. 59(5):746-754 -
Alternative Title:Am J Prev Med
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Personal Author:
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Description:Introduction:
Children at highest risk for obesity include those from certain racial/ethnic groups, from low-income families, with disabilities, or living in high-risk communities. However, a 2013 review of the National Collaborative for Childhood Obesity Research (NCCOR) Measures Registry identified few measures focused on children at highest risk for obesity. Our objective was to 1) Identify individual and environmental measures of diet and physical activity added to the NCCOR Measures Registry since 2013 used among high-risk populations or settings, and 2) Describe methods for their development, adaptation, or validation.
Methods:
We screened references in the NCCOR Measures Registry from January 2013 to September 2017 (n=351) and abstracted information about individual and environmental measures developed for, adapted for, or applied to high-risk populations or settings, including: measure type, study population, adaptation and validation methods and psychometric properties.
Results:
Thirty-eight measures met inclusion criteria. Of these, 30 assessed individual dietary (n=25) and/or physical activity (n=13) behaviors, and 11 assessed the food (n=8) and/or physical activity (n=7) environment. Seventeen measures were developed for, 9 were applied to (i.e., developed in a general population and used without modification), and 12 were adapted (i.e., modified) for high-risk populations. Few measures were used in certain racial/ethnic minorities (i.e., American Indian/Alaska Native, Hawaiian/Pacific Islander, Asian), children with disabilities, and rural (vs. urban) communities.
Conclusions:
Since 2013, 38 measures were added to the Measures Registry that were used in high-risk populations. However, many of the previously identified gaps in population coverage remain. Rigorous, community-engaged methodologic research may help researchers better adapt and validate measures for high-risk populations.
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Pubmed ID:32919827
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Pubmed Central ID:PMC8722431
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