--- description: "There are individuals who are 'activity rich' and individuals who are 'activity poor,' said Stanford bioengineer Scott Delp. title: How Step Count Data Can Predict Obesity image: https://static.time.com/v3/assets/bltea6093859af6183b/bltde093bcdab65f2d0/6988d9b9bc6cfc69913e2a3c/time-logo.jpg?branch=production --- * [Health](/section/health/) ## Health Update your preferences in [Account Settings](/account/preferences/) Close * [Research](/tag/research/) ## Research Update your preferences in [Account Settings](/account/preferences/) Close # How Step Count Data Can Predict Obesity ## Video: Inactivity Worse Than Obesity? [Watch (HLS stream): Inactivity Worse Than Obesity?](https://cdn.jwplayer.com/manifests/19HYwmDb.m3u8) (0:56)  _Published 2015-01-15. University of Cambridge researchers found being inactive may be twice as deadly as being obese._ by [Emily Weyrauch](/author/emily-weyrauch/) ## Emily Weyrauch Update your preferences in [Account Settings](/account/preferences/) Close Jul 10, 2017 4:40 PM CUT by [Emily Weyrauch](/author/emily-weyrauch/) ## Emily Weyrauch Update your preferences in [Account Settings](/account/preferences/) Close Jul 10, 2017 4:40 PM CUT Smartphones could soon be a way for researchers to predict [obesity rates](http://time.com/4475882/obesity-rates-by-state/ "undefined") across the globe, according to a [new study](http://activityinequality.stanford.edu "undefined") published in the journal _Nature_. Of the many things smartphone users can do with their device, they can now track the number of steps they take in a single day. Since a lack of physical activity is a leading risk factor for obesity, researchers from Stanford University teamed up with mobile health startup Azumio to see if variations in step counts could help predict a country’s obesity levels, which is similar to the model used to track income inequality, said Scott Delp, a bioengineer at Stanford and lead researcher on the study. There are some “individuals who are ‘activity rich’ and individuals who are ‘activity poor,'” said Delp. “Countries that have large inequality have a big fraction of the population who are activity poor. And it’s those populations who are really at risk.” Delp and his team tracked physical activity by population in more than 100 countries, including the United States to Norway, India and the Philippines. With data from more than 700,000 anonymous smartphone users, they also looked at users’ age, gender, height and weight. The results revealed that not only could inequality in step counts predict a country’s obesity levels, but in some countries, this “activity inequality” was closely linked to a gender disparity in step count. In countries like the U.S., where there is a greater population of people with obesity, the gap between women’s and men’s activity levels is wider. But in a country like Japan, where the obesity level is low, the activity gap between men and women is much smaller. The study also found that the more walkable a city is, or the easier it is to get around without a car, the less activity inequality that city will have. “What we want to do is understand how we can intervene and motivate healthy activities,” said Delp. One way to do that is to ask how to better design our cities, according to study co-author Jure Leskovec. “How do we make them friendly for pedestrians? If you make them friendly for pedestrians, people seem to walk there more. And that has a connection to obesity and public health.” Leskovec said that this is just the beginning for the possibilities for studies using smartphone data. “Today through the quantified self and through these wearable electronic devices, we are monitoring ourselves 24/7,” said Leskovec. “This is the first study that shows what is possible. It’s clear that this is where the future is.” ```json [{"@context":"https://schema.org","@type":"NewsArticle","@id":"https://time.com/4850108/obesity-rates-smartphones-study/","mainEntityOfPage":{"@type":"WebPage","@id":"https://time.com/4850108/obesity-rates-smartphones-study/"},"headline":"How Step Count Data Can Predict Obesity","datePublished":"2017-07-10T16:40:06.000Z","dateModified":"2026-02-23T16:28:46.001Z","description":"So-called \"activity inequality\" is linked to obesity across different countries","url":"https://time.com/4850108/obesity-rates-smartphones-study/","keywords":["Research","Exercise","Obesity","health","International"],"thumbnailUrl":"","author":[{"@type":"Person","name":"Emily Weyrauch","jobTitle":null,"url":"https://time.com/author/emily-weyrauch/"}],"articleSection":"Health","image":[],"publisher":{"@type":"Organization","name":"Time","url":"https://time.com/","logo":{"@type":"ImageObject","url":"https://time.com/images/logo.png","width":528,"height":156},"foundingDate":"March 3, 1923","sameAs":["https://www.facebook.com/time","https://www.instagram.com/time/?hl=en","https://twitter.com/time","https://www.pinterest.com/timemagazine"]}},{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"/section/health/","name":"Health"}},{"@type":"ListItem","position":2,"item":{"@id":"/tag/research/","name":"Research"}},{"@type":"ListItem","position":3,"item":{"@id":"https://time.com/4850108/obesity-rates-smartphones-study/","name":"How Step Count Data Can Predict Obesity"}}]},{"@context":"https://schema.org","@type":"VideoObject","name":"Inactivity Worse Than Obesity?","description":"University of Cambridge researchers found being inactive may be twice as deadly as being obese.","thumbnailUrl":"https://cdn.jwplayer.com/v2/media/19HYwmDb/poster.jpg?width=720","uploadDate":"2015-01-15T17:35:14.000Z","contentUrl":"https://cdn.jwplayer.com/manifests/19HYwmDb.m3u8","embedUrl":"https://time.com/4850108/obesity-rates-smartphones-study/","duration":"PT56S","potentialAction":{"@type":"SeekToAction","target":"https://time.com/4850108/obesity-rates-smartphones-study/?jw_start={seek_to_second_number}","startOffset-input":"required name=seek_to_second_number"}}] ```