Risk Review

the outcome of the risk review is to make sure that the risk shown matches the user's ethnicity, age, and gender (or other identifying markers) of the study used partners are responsible to ensure the risk study is suitable for it's users partners must be aware of their demographic when calculating risk to make sure the study matches the user's ethnicity, age, and gender (or other identifying markers) health risks are not a "one size fits all" approach ensure the study matches the people who will use the app doing so will ensure an accurate and trusted product by the end of the risk review, the following points should be completed or covered understanding risks not all risks are created equal risks & indicators confirm each risk or indicator study matches your user audience disclaimer addition of disclaimer to app screens where risk is shown tracking risks understanding trends (coming soon) integrating risks information for users (coming soon) understanding risks health risks are the result of applying a study to a set of scan result(s) almost all of the studies used to predict risk are population based researchers gather data related to a specific condition, such as ethnicity, age, height, weight, diet, sleep, family history, blood tests, and other relevant data the results are published showing a strong or weak correlation of this data used for prediction if the study were conducted in north africa, the data would be very accurate and applicable to north africans if applied to europeans/caucasians, it might not be as accurate a study that uses european/caucasians as a cohort would better suit that demographic similarly, if the study involved both men and women over 45 years of age, it is likely to be less effective to those under 45 risks & indicators this step involves making sure the study matches your audience the predictors are the main lead on how this is accomplished where ethnicity is not a predictor, it is likely combined where the difference is small default risks by default, all risks are tailored to a global study (who, idf) or the north american population geographic locations if your app is being released in different geographic locations, it is recommended to use different studies for that unique population to categorize risk e g one for australia aboriginal & torres strait islanders, canada & alaska – aboriginal inuits, etc likewise, where a study might include data for both sexes, there might be a specific study for females it is advised to be specific and use the best study for that sex if it is available conduct frequent risk reviews studies improve over time it is advised to do frequent internal risk reviews so that the predictions are current, and reflect the latest data available obesity risk obesity is a direct relationship to total body fat it is then categorized by age and gender data sheet obesity risk docid\ zfyeukfeyi0386gwlfxa9 about overweight and obesity are defined as abnormal or excessive fat accumulation that presents a risk to health – https //www who int/health topics/obesity#tab=tab 1 predictors by age by sex by total body fat study heo, m , faith, m s , pietrobelli, a , & heymsfield, s b (2012) percentage of body fat cutoffs by sex, age, and race ethnicity in the us adult population from nhanes 1999–2004 the american journal of clinical nutrition, 95(3), 594 602 information the study does split by ethnicity, accounting for only a small difference between the races by using the average of all cutoffs and not asking for ethnicity it can reduce identifiable and race related issues however, partners who have that demographic can use the exact dataset to be closer to the published paper central obesity risk central obesity is a direct relationship to waist circumference it is then categorized by ethnicity and gender data sheet central obesity risk docid\ bzs9ncqxmxpju6nwgk8cm about abdominal obesity, also known as central obesity and truncal obesity, is a condition when excessive abdominal fat around the stomach and abdomen https //www wikiwand com/en/abdominal obesity https //www wikiwand com/en/abdominal obesity predictors by sex by waist circumference by ethnicity europids, south asians, chinese, japanese, ethnic south and central americans, sub saharan africans, eastern mediterranean and middle east (arab) populations study world health organization (2011) waist circumference and waist hip ratio report of a who expert consultation , geneva, 8 11 december 2008 international diabetes federation alberti, g , zimmet, p z , shaw, j , & grundy, s m (2006) the idf consensus worldwide definition of metabolic syndrome information defining central obesity with a simple sex specific waist circumference threshold provides a simple diagnostic and clinical tool to define those who are potentially at greater risk of medical comorbidities, detect them early and facilitate intervention universal cutoffs, covering all ethnicities, are not currently available due to limited research there are inherent challenges related to the determination of health outcomes, including sex differences; age‐related changes in body composition and conformation; and group, population, and geographical differences these confounders need to be evaluated more carefully before consensus cutoffs can be reported type 2 diabetes type 2 diabetes requires self reported information such as diet, family history, physical activity, and information from the bodyscan (waist circumference) this depends on the risk assessment being used, and what can be filled in by a face or body scan it is usually population based, such that the weighting system involved will account for the racial demographic of its occupants data sheet type 2 diabetes docid\ of 0hzpn4d7zmkc9 iwqf risk calculators australia united kingdom idf type 2 diabetes risk predictors (vary based on calculator) by age by weight by sex by family history by diet by activity by ethnicity by smoker study n/a information idf preferred waist circumference waist circumference is a key indicator in multiple risk predictions, in multiple studies some key areas where waist circumference contributes to risk prediction waist circumference is directly interpreted as central obesity risk docid\ bzs9ncqxmxpju6nwgk8cm indicators of abdominal adiposity, especially whtr, are more strongly associated with stroke risk than bmi – https //www ahajournals org/doi/full/10 1161/strokeaha 111 614099 https //www ahajournals org/doi/full/10 1161/strokeaha 111 614099 a waist circumference ≥94 cm in middle aged men, identified those with increased risk for type 2 diabetes and/or cardiovascular disease – https //bmcpublichealth biomedcentral com/articles/10 1186/1471 2458 12 631 https //bmcpublichealth biomedcentral com/articles/10 1186/1471 2458 12 631 predictor for metabolic syndrome to have the metabolic syndrome, a person must have central adiposity defined on the basis of waist circumference and – https //care diabetesjournals org/content/28/11/2745 https //care diabetesjournals org/content/28/11/2745 it is advised to use waist circumference as a single, key indicator for central obesity waist circumference docid 7aka qjarwucsjyenot3v where cardiovascular health or metabolic syndrome is included, highlight its importance along with waist hip and waist height indicators waist hip ratio the waist hip ratio is a direct relationship to waist and hip circumference it is categorized by ethnicity and sex data sheet waist hip ratio docid\ czukvsxdueuhz4fkxcl3w about the waist hip ratio is used to measure risks of chronic disease and mortality a larger waist to hip ratio indicates preferential fat storage around the waist in the form of visceral adipose tissue, which can be associated with increased disease and mortality risk predictors by waist circumference by hip circumference by sex by ethnicity united states, europids, middle east, african, south and central americans, south asian, chinese, japanese study waist circumference and waist hip ratio report of a who expert consultation – world health organization information waist height ratio the waist hip ratio is a direct relationship to waist circumference and height (self reported) it is categorized by sex data sheet waist height ratio docid\ mjymhpgqk 6p7davaglxn about a larger waist to height ratio can be associated with higher levels of abdominal fat in the form of visceral adipose tissue which is linked to increased risks of chronic disease and mortality it is recommended to keep your waist circumference to less than half your height for improved health predictors by waist circumference by height by sex study ashwell, m , gunn, p , & gibson, s (2012) waist‐to‐height ratio is a better screening tool than waist circumference and bmi for adult cardiometabolic risk factors systematic review and meta‐analysis obesity reviews, 13(3), 275 286 information as height is self reported, it might suffer from human error due to the nature of the cutoffs, it might have negligible effects disclaimer smartphone based imaging systems for fitness, health, and medical applications are relatively new, despite the smartphone being widely used for a range of medical purposes completescan and its prediction of risks is not been approved as a medical device a disclaimer must be added to be transparent with end users this content is for informational purposes only and is not a substitute for the judgment of a healthcare professional it is intended to improve awareness of general wellness reading smartphone based imaging systems for medical applications a critical review brady hunt, alberto j ruiz, brian w pogue