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8min

Weight Prediction

Data Type

Health Indicator

Scan Requirements

BodyScan

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/

Other Articles of Interest

The reliability and validity of self-reported weight and height

Biases in self-reported height and weight measurements and their effects on modeling health outcomes

Comparisons of Self-Reported and Measured Height and Weight, BMI, and Obesity Prevalence from National Surveys: 1999–2016

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

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

Updated 10 Jun 2022
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TABLE OF CONTENTS
Agreement of anthropometric and body composition measures predicted from 2D smartphone images and body impedance scales with criterion methods
Other Articles of Interest
The reliability and validity of self-reported weight and height
Biases in self-reported height and weight measurements and their effects on modeling health outcomes
Comparisons of Self-Reported and Measured Height and Weight, BMI, and Obesity Prevalence from National Surveys: 1999–2016
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
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