Smartphones provide info for combating obesity
Dataset on steps walked is the largest collected in such a systematic way, says NIH’s Grace Peng.
Smartphone data collected from more than 700,000 people in 111 countries shows worldwide inequality in physical activity, which is a good predictor of obesity.
Findings from the global human movement study, conducted by National Institutes of Health-funded researchers at Stanford University, were published last week in the journal Nature in an effort to prevent the more than 5 million deaths annually from causes associated with inactivity.
By publishing the data on how countries, genders and community types fare in physical activity, researchers hope that public health officials will be able to launch intervention initiatives around the world that lead to improved health outcomes for their respective populations.
Also See: Physician willingness to use wearables data in treatment grows
Leveraging ubiquitous smartphones with built-in accelerometers to measure physical activity on a global scale, the study reveals inequality in how activity is distributed within countries and that this inequality is a better predictor of obesity prevalence in the population than average activity volume.
“Reduced activity in females contributes to a large portion of the observed activity inequality,” conclude the researchers. “Aspects of the built environment, such as the walkability of a city, are associated with a smaller gender gap in activity and lower activity inequality. In more walkable cities, activity is greater throughout the day and throughout the week, across age, gender and body mass index (BMI) groups, with the greatest increases in activity found for females.”
Part of NIH’s Big Data to Knowledge initiative—designed to better analyze and leverage a growing tsunami of biomedical datasets—Stanford’s Mobilize Center received an NIH grant as a Center of Excellence for Big Data Computing to conduct the study.
“It is a very large dataset and probably the largest collected in such a systematic way,” says Grace Peng, director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis. “The whole purpose of these Centers of Excellence is to develop new data science and analytical tools to analyze the data.”
Peng adds that the Stanford Mobilize Center is unique in that its investigators are world-renowned researchers in studying human movement. For this study, she notes that they used the Gini index, a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents, to calculate activity inequality by country.
“They measured physical activity, as measured by steps, in different cities around the world” resulting in a dataset consisting of 68 million days of physical activity for 717,527 people, according to Peng, who says that participants whose data contributed to this study subscribed to the Azumio Argus app—a free app for tracking physical activity.
What researchers discovered is that people in the five countries with the greatest activity inequality are nearly 200 percent more likely to be obese than individuals from the five countries with the lowest activity inequality. In addition, investigators reported that countries with greater activity variation also have a larger proportion of inactive women.
They also found that in countries where activity is more uniform among members of the population, such as Japan, males and females are similarly active. However, in countries with greater activity disparity, such as Saudi Arabia and the United States, there is disproportionately reduced activity for females. In fact, researchers revealed that the gender gap accounts for 43 percent of activity inequality in those countries.
Further, the data showed that the prevalence for obesity increases faster for females than males as population-wide activity decreases. At the same time, researchers discovered that “aspects of the built environment, such as the walkability of a city, are associated with a smaller gender gap in activity and lower activity inequality.”
According to Peng, the “walkability” of a city is defined by the authors as an environment that is safe and enjoyable to walk in, and that higher walkability is associated with significantly more daily steps across all age, gender, and BMI categories.
“This technology that we all have is providing insight into movement around the world and how countries compare,” she concludes. “Relating it to obesity is interesting because it can tell us about our health. But, there’s still a lot remaining to make those correlations exactly.”
Findings from the global human movement study, conducted by National Institutes of Health-funded researchers at Stanford University, were published last week in the journal Nature in an effort to prevent the more than 5 million deaths annually from causes associated with inactivity.
By publishing the data on how countries, genders and community types fare in physical activity, researchers hope that public health officials will be able to launch intervention initiatives around the world that lead to improved health outcomes for their respective populations.
Also See: Physician willingness to use wearables data in treatment grows
Leveraging ubiquitous smartphones with built-in accelerometers to measure physical activity on a global scale, the study reveals inequality in how activity is distributed within countries and that this inequality is a better predictor of obesity prevalence in the population than average activity volume.
“Reduced activity in females contributes to a large portion of the observed activity inequality,” conclude the researchers. “Aspects of the built environment, such as the walkability of a city, are associated with a smaller gender gap in activity and lower activity inequality. In more walkable cities, activity is greater throughout the day and throughout the week, across age, gender and body mass index (BMI) groups, with the greatest increases in activity found for females.”
Part of NIH’s Big Data to Knowledge initiative—designed to better analyze and leverage a growing tsunami of biomedical datasets—Stanford’s Mobilize Center received an NIH grant as a Center of Excellence for Big Data Computing to conduct the study.
“It is a very large dataset and probably the largest collected in such a systematic way,” says Grace Peng, director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) program in Computational Modeling, Simulation and Analysis. “The whole purpose of these Centers of Excellence is to develop new data science and analytical tools to analyze the data.”
Peng adds that the Stanford Mobilize Center is unique in that its investigators are world-renowned researchers in studying human movement. For this study, she notes that they used the Gini index, a measure of statistical dispersion intended to represent the income or wealth distribution of a nation's residents, to calculate activity inequality by country. “They measured physical activity, as measured by steps, in different cities around the world” resulting in a dataset consisting of 68 million days of physical activity for 717,527 people, according to Peng, who says that participants whose data contributed to this study subscribed to the Azumio Argus app—a free app for tracking physical activity.
What researchers discovered is that people in the five countries with the greatest activity inequality are nearly 200 percent more likely to be obese than individuals from the five countries with the lowest activity inequality. In addition, investigators reported that countries with greater activity variation also have a larger proportion of inactive women.
They also found that in countries where activity is more uniform among members of the population, such as Japan, males and females are similarly active. However, in countries with greater activity disparity, such as Saudi Arabia and the United States, there is disproportionately reduced activity for females. In fact, researchers revealed that the gender gap accounts for 43 percent of activity inequality in those countries.
Further, the data showed that the prevalence for obesity increases faster for females than males as population-wide activity decreases. At the same time, researchers discovered that “aspects of the built environment, such as the walkability of a city, are associated with a smaller gender gap in activity and lower activity inequality.”
According to Peng, the “walkability” of a city is defined by the authors as an environment that is safe and enjoyable to walk in, and that higher walkability is associated with significantly more daily steps across all age, gender, and BMI categories.
“This technology that we all have is providing insight into movement around the world and how countries compare,” she concludes. “Relating it to obesity is interesting because it can tell us about our health. But, there’s still a lot remaining to make those correlations exactly.”
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