Thursday, February 14, 2013

Feel fat, depressed and unhealthy? Get off your tookus!

If you're like most people, you spend your entire day at a desk and 3-4 hours a week at a gym trying to combat the negative effects associated with sitting at that desk.  As time has gone on, you've probably also noticed a reduced ability to maintain your body weight as well as increased risk markers for cardiovascular disease and other chronic diseases.  Even when you double up the amount of time you exercise per week for your New Years' resolution your results get worse each year, leading to year over year increases in fat mass.  The reason this happens is not because you don't exercise enough, it's because you spend too much time sitting.  Sedentary behavior leads to modified genetic expression that promotes fat gain and cardiovascular disease, and no amount of exercise at a gym will prevent that.  When you look at the grand scheme of things, even if you exercise intensely for 16 hours a week that still leaves 152 hours per week where the wrong genes are turned on.  Don't believe it?  Let's take a look at some of the research.

High levels of sedentary behavior are associated with the metabolic syndrome, independent of other factors related to the metabolic syndrome including moderate to vigorous physical activity(Alcohol intake, smoking status, age, gender, diabetes and heart disease)(1, 2).  This means that getting physical activity via exercise did not compensate for the amount of time spent being sedentary.  The amount of sedentary time also has a strong positive relationship with triglyceride levels as well as waist circumference and waist to hip ratio.  High levels of sedentary time also lead to higher circulating levels of insulin(3, 4, 5, 6, 7, 8), impaired glucose clearance(3, 7, 8)  and impaired fatty acid metabolism(5, 7, 8).  While a couple of these studies were done with people on multiple days of bed rest and therefore not directly comparable to people sitting at a desk day in and day out, most of these changes with insulin action and glucose appear to be a result of changes in localized gene expression due to a lack of muscular contraction(7).  In fact, as discussed in Part 2a of my 3 part series "Myths, Metabolism, and Appetite" (Part 2a), it may actually be whether or not the leg is loaded, regardless of muscular contraction.  Unloading one leg while still allowing movement of that leg for 48 hours leads to altered genetic expression that increases protein breakdown and anti-oxidant pathways (Indicating increased oxidative stress) while reducing mitochondrial metabolism with no change in gene expression in the other leg(9).  This reduction is mitochondrial metabolism is probably the mechanism by which fatty acid metabolism is reduced during sedentary periods.  These changes persisted even after 24 hours of reloading the leg.

When we look at who is most affected negatively by sedentary behavior from an insulin sensitivity perspective, it appears that healthy people are more negatively impacted than people prone to Type 2 Diabetes (T2D).  In a study that looked at bed rest and changes in insulin sensitivity with healthy people as well as people with first degree relatives with T2D (FDR)and those with low birth weight, two risk factors for T2D, the healthy subjects experienced a greater drop in insulin sensitivity (5).  The authors hypothesize that this effect is due to the other two groups already having some degree of insulin resistance. In another study comparing insulin sensitivity changes in healthy subjects to FDR, whole body insulin sensitivity declined in both groups but hepatic (Liver) insulin sensitivity declined only in the FDR group.  This is interesting because as discussed in "Myths, Metabolism, and Appetite", people who are prone to T2D and FDR of T2D have fewer type I fibers and a higher proportion of type IIx muscle fibers.  This is, in part, a gene environment interaction.

While the more oxidative (Fat burning) type I fibers have not been shown to convert to other fiber types, the more glycolytic (Glucose burning) type IIa and IIx fibers tend to convert back and forth based on recruitment of said fibers.  Lack of use causes IIa fibers to convert to IIx fibers which are more insulin resistant while regular recruitment of IIx fibers causes them to convert to IIa fibers.  In people with a higher percentage of type II vs. type I muscle fiber types that also do not recruit these fibers regularly, most will become insulin resistant as more of their musculature converts to the insulin resistant type IIx fibers.  People with this genotype probably have to participate in regular strength training to recruit the insulin resistant IIx fibers enough so that they convert to the less insulin resistant IIa fibers, particularly if they intend to consume a high carbohydrate diet.  Coincidentally, converting IIx fibers to IIa fibers allows these people to store more muscle glycogen.  Emptying out these glycogen stores with regular, intense strength training will provide a larger storage compartment for ingested carbohydrate and delay hepatic insulin resistance.  Ironically enough, people with this genotype tend to be the better power sport athletes so it seems that modern life is just not compatible with this genotype.  My guess is they would also have been the best hunters which could indicate why such a high percentage of the population is prone to T2D from an evolutionary perspective.

Another interesting aspect of sedentary behavior is it's effects on lipoprotein lipase(LPL) activity.  LPL is an enzyme responsible for triglyceride breakdown.  Reduced LPL activity leads to higher blood triglycerides via a reduced ability to metabolize fat.  Obviously conditions that lead to a reduction in LPL activity are not ideal, especially if one of your goals is to reduce body fat.  Sedentary behavior has been shown to dramatically lower LPL activity (6, 7) in the muscles of the leg and reducing sedentary behavior has been shown to have a greater effect on increasing LPL activity than does adding vigorous physical activity (7).  This increase in LPL activity makes sense because the muscle fiber type associated with physical activity of lower intensities is the type I fibers that tend to rely more on fat as a substrate.  As the intensity of your exercise increases, so does the utilization of glucose as fuel to power the type II fiber types during that activity.  During both active and passive recovery there appears to be a switch to the type I fibers and a greater reliance on fat as fuel, perhaps to spare glucose for future intense activity.

Other genes and pathways associated with health are positively affected by breaking up periods of inactivity.  One study identified 75 different genes differentially expressed during periods of inactivity vs. periods of activity used to break up inactive periods (8).  Many of these genes are involved in processes that are known risk factors for cardiovascular disease.  Breaking up periods of inactivity with periods of physical activity for 2 minutes every 20 minutes positively affected the expression of genes associated with carbohydrate metabolism, antioxidant pathways and anti-inflammatory pathways.  Another study found breaking up periods of inactivity improved postprandial insulin and glucose concentrations when compared to a completely sedentary condition(9).  While we have focused much of our attention on the localized effect of sedentary behavior on muscles and to a lesser extent the liver, there also appears to be a significant negative impact on the brain.

Increased sympathetic nervous system activity is a widely known symptom of obesity and T2D.  The autonomic nervous system is in charge of regulating mostly involuntary processes and has two branches.  The parasympathetic branch is responsible for rest and digest while the sympathetic nervous system is responsible for the fight or flight response.  People with increased sympathetic nervous system activity have a problem getting out of stress mode, in other words they are in a constant state of stress.  Research indicates that this increased sympathetic activity may be mediated by dysfunction in a part of the brain called the rostral ventrolateral medulla (RVLM)(10).  The RVLM is the primary part of the brain involved in regulating sympathetic nervous system activity.  Physical inactivity may have wide-ranging negative effects on the RVLM and this could explain the detrimental effects of sedentary behavior on measures of cardiovascular disease regulated by the autonomic nervous system such as hypertension.  It is not known at this point if the difference between sedentary and active people is due to a negative effect of being sedentary, a positive effect of being active, or a combined effect of the two.

As you can see, being in a seated position for prolonged periods is a significant factor in poor health and an inability to metabolize fat.  While insulin sensitivity and blood glucose utilization are two big factors impacting both, these are not the only considerations.  The data suggests that sitting for long periods of time is terrible for your health and no amount of exercise at the gym can attenuate the bad effects of sitting.  These effects may expand beyond the physical changes happening in the muscles and more than likely has deleterious effects on the brain.

EDIT: After I wrote this I found a new randomized clinical trial that looked at 3 groups (sedentary, sedentary+1 hour of intense exercise, and a group that spent half the time being sedentary and the other half standing or doing low intensity activity).  Guess who "won".  :)

Check it out.

Tuesday, February 12, 2013

Cholesterol Screening: A cost to benefit analysis

As more and more employers realize the importance of maintaining a healthy working staff, the number of companies participating in cholesterol screening as part of a risk assessment protocol has increased.  There are obvious financial and ethical benefits to having happy, healthy workers.  A happier worker is more productive and tends to cost less from a health insurance standpoint.  The problem is, will cholesterol screening actually achieve that stated goal?  In other words, if I put my worker bees through a cholesterol screening, will this save me some scratch?  Let's explore this a little further.

The point of putting workers through a cholesterol screen is to identify those who are at risk for heart disease and/or future coronary events.  Once identified, these people will be put on the appropriate therapy to ensure that they avoid experiencing the big one and needing the higher medical costs of dealing with the problem as it arises.  In other words, we can all agree that an ounce of prevention is worth a pound of cure.  However, let's see if that is actually what we are accomplishing.

Unless you have been hiding under a rock for the past several decades you have heard of statin drugs.  Statin drugs are currently the standard of care for treating people with heart disease, despite there being no real evidence that they prevent heart attacks in anyone other than middle aged men who have already had a heart attack.  In this very small sample of people, cholesterol screenings are unnecessary because these men are already on statins.  For the remainder, let's take a look at what you are buying in to.

Let's say I have a large business with 1000 employees who are not currently on statins and they all sign up for cholesterol screening.  The criteria for high cholesterol puts approximately 1 in 3 people in this group, so let's say 333 of your employees are diagnosed with high cholesterol.  Most physicians will not prescribe a statin based solely on high cholesterol, so let's assume only 200 of your employees are recommended to take statin drugs.  What can we expect to see in terms of results?

If you listen to the way these drugs are marketed, you would realize that statins reduce heart attack risk by 36%, but what does this mean in a way that is pertinent to our discussion?  Probably the most clear cut way would be to look at a number that gives you the risk to benefit ratio.  In the pharmaceutical world, this is referred to as the number needed to treat (NNT).  The NNT is the number of people you would need to treat with the drug in order to prevent 1 person from experiencing the adverse event you are trying to prevent.  In other words, in the case of statins, the NNT is the number of people you would need to treat to prevent 1 heart attack.  When we look at this number, we get a much clearer picture of what we are getting.  The NNT to prevent 1 heart attack varies between 70-250 people depending on the study you look at.  When you take in to consideration that this NNT also includes people who have already had a coronary event, the NNT for people that will be undergoing cholesterol screening is closer to 1 in 250.  In other words, 249 of the people you are treating with this drug are not benefiting from taking it.  Furthermore, you would need to treat all 250 of these people for 5 years with the drug before you would prevent that 1 heart attack.

It is highly likely that every one of the 200 employees you have identified as candidates for statin therapy will receive no benefit from the drug, and you as well as they get to pay for that therapy.  In addition, recent research has shown that statin therapy induces diabetes in 1 out of 200 people taking the drugs.  So, while you have prevented zero heart attacks you have actually increased your healthcare costs by adding a diabetic to the payroll.  By the way, people with Type 2 Diabetes have the same risk of heart attack or dying from heart disease as people who have already had a heart attack.  Framed in that context, does that cholesterol screening really sound like something that is going to prove beneficial to your organization or does it seem more like a way to sell you something that is not really going to benefit you at all?

There is, of course, very large healthcare costs associated with someone experiencing a heart attack.  You may even hear that spending all of that money treating people with a drug that is not benefiting them in any way may make sense when you look at the cost savings of preventing a heart attack.  Ethical considerations aside, this benefit does not exist.  High cholesterol isn't even a good indicator of future heart disease.  The actual data shows that 50% of the people who die of heart disease have normal cholesterol.  In other words, you are financing a screen that has the same likelihood of predicting a heart attack as a coin flip, and investing a large sum of money in it's ability to do that.