Evaluation And Analysis Of The Effect Of Weight Reduction Program For A Mechanism Based On Body Fat Scale Measurement Data

Obesity has been defined as a chronic noncommunicable disease for more than 70 years.It causes a variety of cardiovascular diseases,chronic metabolic diseases,cancers including breast and colon cancer,and digestive diseases.There is also evidence that obese people are more likely to die prematurely.Obesity,together with a series of chronic diseases caused by it,has seriously threatened people's health.Obesity can be caused by many factors,such as too many calories,too much sitting and too little exercise,and genetic factors.As the progress of all sorts of relevant research and people are taller and taller to healthy take seriously degree,reduce weight also became healthy sign,the product reducing weight that extends from this also multifarious.Drugs,fitness,diet and other ways to lose weight have also become the most popular choices.However,it is not known whether drug weight loss will affect users' health.How to safely and quickly lose excess fat and reduce the impact of obesity on health is currently a hot topic.Many health management agencies also target this promising market,through external equipment monitoring of its user data,coupled with scientific guidance program,to help users achieve the goal of weight loss.In order to study the users of such weight loss platform,study the effect and scientificity of the scheme provided by the institution,and help different users develop personalized weight loss scheme,this paper intercepts part of user data of a fitness platform to study the influencing factors of weight loss rate under the same scheme.The results showed that under the same weight loss program,male users lost weight faster than female users.With the increase of age,the rate of weight loss shows a decreasing trend.Users of different genders and ages have different body indexes before and after weight loss.In order to give differentiated opinions to different users,the user data intercepted by the platform was finally divided into four categories by k-means clustering method to analyze the changes of body indexes before and after weight loss of various users.Based on the original scheme,corresponding supplementary opinions were given to the changes of body indexes of different users.