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Predictors of Persistent Body Weight Misclassification from Adolescence Period to Adulthood: A Longitudinal Study
This study examined whether body weight misclassification continues from adolescence to adulthood and the associated predictors behind that misclassification. Data are from a sample of a longitudinal Australian birth-cohort study. Data analyses were restricted to 2938 participants whose measured and...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Atlantis Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7310748/ https://www.ncbi.nlm.nih.gov/pubmed/31241869 http://dx.doi.org/10.2991/jegh.k.190518.002 |
Sumario: | This study examined whether body weight misclassification continues from adolescence to adulthood and the associated predictors behind that misclassification. Data are from a sample of a longitudinal Australian birth-cohort study. Data analyses were restricted to 2938 participants whose measured and perceived body weights were recorded during their adolescence and adulthood follow-ups. To identify misclassification, we objectively compared their measured and perceived body weights at each follow-up. Potential predictors during early life or adolescence periods were included in data analyses. At each follow-up, underestimation was recorded more often among overweight and obese participants, whereas overestimation was mostly recorded among underweight ones. Over 40% males and females were able to correctly estimate their body weight at one follow-up, whereas almost 30% males and 40% females were able to do so in more than one follow-ups. One-third females and 45% males underestimated their body weight at one follow-up, whereas 13% females and a quarter of males were able to do so in more than one follow-ups. Being female, dieting, being overweight, having an overweight mother, and having poor mental health were the most significant predictors for more than one follow-up misclassifications. Further studies are needed to evaluate the impact of persistent misclassification on population health benefits. |
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