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Posts Tagged ‘Obesity’

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Hold on to your hats folks, this is not good news…

Monday, July 11th, 2011

Kulkarni et al., Popul Health Metr. 2011

Over the years, the life expectancy of an adult in the US has increased dramatically. It is almost a law of nature that with advances in medicine, nutrition, and public health (vaccinations, etc.) life expectancy increases over time. A decrease in life expectancy is a sign of something going seriously wrong.

The figure above is from a recently published paper titled, “Falling behind: life expectancy in US counties from 2000 to 2007 in an international context.” It shows changes in life expectancy for women from 1987 to 2007. You will note from the figure legend that the red on this map depicts counties in which the change was less than zero. That means that the life expectancy of women in those counties has decreased over the past two decades.

This comes on the heels of a report from the Robert Wood Johnson Foundation titled, “F as in fat: How obesity threatens America’s future.” Here are a few tidbits:

  • Colorado is the only state with an obesity rate below 20% (coming in at 19.8%)
  • A state at 19.8% obesity would have had the highest rate in 1995
  • No state has had a decline in the rate of obesity
  • Over the past 15 years, rates of obesity have doubled in seven states and rates of diabetes have doubled in 10 states

We are experiencing a crisis – and we need to make some changes. There will be no single solution, rather we will have to change our behaviors, policies, environments, practices, etc.

What are you going to change today?

“Eat Less and Exercise More” is Not Good Enough

Monday, June 27th, 2011


(Mozaffarian et al., NEJM 2011)

There is a recent paper out in the New England Journal of Medicine in which the investigators examined relationships between diet, behaviors, and weight over time frames of 10-20 years in over 120,000 adults in the US. The investigators found that people gained an average of 3.35 pounds every four years and that weight gain was significantly associated with higher consumption of potato chips, potatoes, sugar-sweetened beverages, unprocessed red meats, and processed meats (see figure above). Weight gain was inversely associated (less weight gain with greater consumption) with consumption of vegetables, whole grains, fruits, nuts, and yogurt.

So, you might be asking yourself – what’s the big deal? How did this paper get into a top-tier journal by confirming what we all already know – that chips and soda are bad for you and fruits and vegetables are good for you? Well, here are a few additional findings and speculations that I think make the paper more interesting than the “potato chip findings” that have been grabbing the headlines.

One of the strengths of this type of work is that the authors have looked at data for a huge number of people. This increases the likelihood that the findings have external validity or that they will be generalizable to the population at large. However, a limitation to this type of study (observational, not interventional or controlled) is that we can only make correlational inferences or talk about “associations” and not “causes.”

“You want fries with that?”

What is the “that?” It might be the case that certain types of foods are more likely to be eaten together (think burger and fries). The authors reported that there were only a few correlations between food types. For example, people more likely to eat vegetables were also more likely to eat fruit. Likewise, people more likely to eat unprocessed red meat were also more likely to eat processed meats. And, people more likely to consume low-fat dairy were less likely to consume high-fat dairy. These sorts of findings seem to make sense, probably because we largely recognize that meat of one type can often substitute for meat of another type and that dairy of one type can often substitute for dairy of another type. Less clear, however, is which foods might be serving as economic complements. The consumption of a complement is typically tied to something else. For example, you probably eat very few hot dog buns in the absence of hot dogs – the bun is an economic complement. This brings us back to the question of whether you want fries with that and what is the “that?” Chips and fries often accompany burgers, sandwiches, and sodas. Chips make people thirsty and I rarely see chips paired with water, coffee, tea, or milk. So, perhaps what we’re looking at here is clusters of foods or behaviors.

Another way to think about this is to ask yourself what percentage of chips or fries that you have eaten did you make yourself at home? It is likely that fries are often associated with eating on-the-go and chips are often associated with convenience stores and impulse purchases. True, the chips and fries don’t help, but they alone are not the entire story.

So, where do we go from here? It’s an interesting exercise to think about what foods and behaviors in your life tend to be complements or are associated with each other. It is also interesting to think about foods and behaviors that you might be able to substitute for one another to help you achieve your goals (e.g., a piece or fruit or yogurt in place of a sweet or dessert). If certain foods and behaviors are clustered together, a couple of initial substituions could help the whole house of cards begin to fall…  


Thursday, June 2nd, 2011

In the classic 1984 movie Gremlins, there are three basic rules that are are explained for keeping a Mogwai (pictured above) as a pet.

1. Don’t get him wet

2. Keep him away from bright lights

3. Don’t feed him after midnight

As you know from the movie, feeding after midnight can have disastrous consequences. In a new study out of Northwestern University, it looks like staying up late and eating after 8:00 PM can also go a long way to derail your effort to achieve and sustain your ideal weight.

Sleep duration, or the number of hours you sleep each night, has been linked to obesity. That is to say that people who get less sleep on average, are more likely to be overweight or obese. However, less is known about how the timing of your sleep might affect your weight. Different people keep different schedules due to work or other responsibilities and some people just feel that they are naturally a “morning person” or a “night person.” The goal of the study that we’re talking about today was to see how sleep schedules affect dietary patterns and BMI.


(Figure 1 from Baron et al., 2011)

The study looked at the sleep and eating habits of 52 people (25 females) over a week. They characterized half of the people as “normal sleepers” who tended to go to sleep around 12:30 AM and wake up around 8:00 AM (see the figure above for average sleep, wake, and meal times). The other half of the participants were characterized as late sleepers who tended to go to sleep around 3:45 AM and wake up around 10:45 AM (note the total hours of sleep time are pretty similar). Take a look at the figure and see which group would you most likely fall into.


(Table 3 from Baron et al., 2011)

The authors found that compared to “normal sleepers,” “late sleepers” consumed significantly more calories at dinner, ate more fast food, drank more pop (soda for you folks not from the Midwest), and ate fewer servings of fruits and vegetables (see table above). When subjected to fancy statistical models, the data showed that higher numbers of calories consumed after 8:00 PM were predictive of higher BMI’s, even after controlling for sleep timing and sleep duration. Thus, it appears as though there is an independent risk for weight gain associated with eating after 8:00 PM. But, why did this affect the types of things consumed? Perhaps fast food is more available and fruits and vegetables less available in the evenings? Or was there a potential interaction between sleep and decision making? In any case, there are interesting future questions to be asked, but in the interim, the authors suggest that regulating the timing of your eating and sleeping could improve the effectiveness of your efforts to achieve or sustain your ideal weight.

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