Weight Prediction

false false unhandled content type unhandled content type unhandled content type unhandled content type ahi weight prediction offers a way to check self reported weight through a bodyscan as weight is a major component in calculating total body fat determining health risks, an incorrect body weight can lead to miscalculation bias exists in a lot of individuals to some degree most people do not weight themselves eveery day and will recall the last time their weighed themselves some overweight and obese individuals might under report their weight, leading to a lower risk similaraly, there are cases where individuals are underweight and over report their weight bmi remains an important indicator for underwriting pricess in life & health insurance misreported weight will lead to higher premiums as individuals will be miscategorized and lead to incorrect premium pricing intervention will not be possible to help those individuals, leading to late claims and increased risk of mortality weight prediction allows partners to compare self reported weight with a prediction and flag the result as a mis reported value agreement of anthropometric and body composition measures predicted from 2d smartphone images and body impedance scales with criterion methods body composition and anthropometry assessment from two dimensional smartphone images is possible through advancement of computational hardware and artificial intelligence (ai) techniques this study established agreement of a novel smartphone assessment, compared with traditional bioelectrical impedance analysis (bia), and criterion measures https //pubmed ncbi nlm nih gov/35094958/ https //pubmed ncbi nlm nih gov/35094958/ other articles of interest the reliability and validity of self reported weight and height the reliability and validity of measures of self reported weight and height are analyzed by using data on 3373 people 14–61 yr of age results indicate that these measures are remarkably accurate indicators of actual weight and height the measures are valid and reliable, even in groups of people for whom one might expect the data to be of a poorer quality, such as those who are severely overweight nevertheless, there are some group differences in reliability and validity that may be important in some types of studies read more biases in self reported height and weight measurements and their effects on modeling health outcomes self reported anthropometrics are often used as proxies for measured anthropometrics, but research has shown that heights and weights are often misreported using the study on global ageing and adult health, i analyze misreporting patterns of height, weight, and bmi in china, india, russia, and south africa adjustments of self reported heights and weights using demographic, social, and anthropometric characteristics are evaluated and found to be useful in studying the distribution of anthropometrics within a population measured, self reported, and adjusted bmi are then compared in logistic regression models on the reporting of health outcomes, as well as the resulting accuracy of individual prediction when bmi is used as a continuous variable in models of health outcomes, measured, self reported, and adjusted bmi produce similar coefficient estimates, and so self reported data would be a natural choice because of its accessibility and convenience in other applications, such as models using categorical bmi and individual prediction using either continuous or categorical bmi, self reported data in lieu of measured data might not be accurate enough, but adjustments could serve as a potential compromise read more comparisons of self reported and measured height and weight, bmi, and obesity prevalence from national surveys 1999–2016 the aim of this study was to compare national estimates of self reported and measured height and weight, bmi, and obesity prevalence among adults from us surveys read more pns117 correlation between self reported and clinical measures of weight, height and body mass index in adults members of a private health insurance company in colombia, 2019 objective is to determine the correlation between weight, height and body mass index (bmi) self reported and clinically measured in members of a private health insurance company in colombia read more pns117 correlation between self reported and clinical measures of weight, height and body mass index in adults members of a private health insurance company in colombia, 2019 objective is to determine the correlation between weight, height and body mass index (bmi) self reported and clinically measured in members of a private health insurance company in colombia read more