Sorry for the wholesale copy and paste but this offers a good prism to view Nashville.
https://arstechnica.com/science/2017/07/physical-activity-inequality-can-explain-obesity-differences/
SCIENTIFIC METHOD —
Physical activity inequality can explain obesity differences
On average, people in the US take around the same number of steps daily as people in Mexico—about 4,700. But the US has a much higher obesity rate than Mexico—27.7 percent compared to 18.1 percent. Why?
The immediate and obvious answer is food culture, and that probably does play an important role. But a paper in Nature this week suggests something else we should be looking at: activity inequality. In the US, a small section of the population gets in lots of daily activity, dragging the average higher, but the majority of people get very little. Other countries, like Japan, are more equal: more people there tend to fall around the average.
Activity inequality is already part of the conversation about obesity. When we talk about problems like
exercise deserts, we’re talking about how some groups of people live in situations where there aren’t many options for physical activity, leaving a portion of the population with below-average activity. A new look at global data, however, confirms that this is a vital way to analyze the problem: high activity inequality in a country means high obesity, much more reliably than low average-activity levels mean high obesity. And addressing this inequality specifically, rather than looking at average activity, could yield much greater results.
How much do people move? Hard to say
Without good evidence on physical activity, policy decisions have to be based on educated guesses and assumptions. But good data on physical activity is very difficult to get. You can ask people to report how much activity they’re getting, but self-reports are notoriously unreliable (almost everyone says they get more exercise than they do). You can give a whole bunch of research subjects wearables, but the data will be limited by how many wearables you hand out and who gets them.
The huge number of people now tracking their activity through various apps and wearables is a data goldmine for getting actual, solid numbers on physical activity worldwide. Computer scientist Tim Althoff and a team of researchers at Stanford used data from more than 700,000 users of smartphone activity-tracking app Argus, from 68 million days of activity tracking, to observe the activity patterns of people from around the world.
There are obviously some important gaps in this data. The researchers looked only at data from iPhone users and focused on countries with more than 1,000 Argus users. That meant a mix of 32 high-income countries (like the US and Japan) and 14 middle-income countries (like China and South Africa). No low-income countries were in the mix.
It also means that users overall were probably on the wealthy side. That’s especially the case for middle-income countries (where iPhones are more likely to be owned by only wealthier individuals) than high-income countries where they tend to be a bit more ubiquitous. And importantly, every single Argus user cared enough about their health to download a smartphone app that tracks their movements throughout the day. Those people might not be perfectly representative. But no data set is perfect, and fitness tracking data is a big jump up from self-reporting.
Hostile cities
So what leads to this activity inequality? The answer is definitely complicated, but this data set confirmed that the built environment is an important contributor. The researchers looked at the walkability of 69 cities in the US and found that people who lived in walkable cities—those with parks and shops within walkable distance, as well as short, walkable blocks—got more steps in on weekdays as well as weekends. Activity inequality in these cities is lower, and that includes both poorer and wealthier cities.
Gender also plays a role: there’s a walking gender gap, with men getting in more steps than women. And countries with higher activity inequality also have a bigger gender gap. As with everything else, the causes of this are likely to be hugely complex, but the built environment plays a role here too. Cities that are more walkable have a smaller gender gap.
Women and men have different responses to inactivity. Men who walk 10,000 steps a day have a lower rate of obesity (about 20 percent) than men who walk 1,000 steps a day (about 30 percent). Obviously. But for women, that curve is a lot steeper: from about 10 percent obesity at 10,000 steps a day, with a sudden upward rise at 5,000 steps a day or fewer. At 1,000 steps a day, women’s obesity levels have slightly overtaken men.
All of this is important because it pinpoints where effort could be invested to have the biggest public health impact. Improving the built environment should help to close the gender gap and reduce activity inequality overall, which in turn should have marked impacts on obesity levels.
In fact, the researchers used the data to predict what would happen if everyone got an extra 100 steps a day (increasing average activity), compared to what would happen if the least-active people got a big jump up with 500 extra steps. Focusing on average activity level would reduce obesity levels by about 2.3 percent, but reducing inequality would have a much bigger impact: approximately 8.3 percent.
Many of these findings confirm the results of other research done with less robust data. Obviously, more research will be needed, with other datasets that have different weaknesses, letting researchers slowly circle in on the truth over time. But these results point to a small but vital change in the way we should think about the problem.Unwalkable cities, activity inequality, and obesity are a tricky blend.
