I've not fallen off the edge of the world

I've been rowing, and roller skiing, and hiking, and building trails, and even started running again this week. But mostly I've been resting and, after a long absence, contributing to my where's the beef blog.

1. on why I got a metatarsal stress fracture

2. a long and not very user-friendly (unless you like statistics) review of the most incompetent published paper that I've read.

I also came across a really well written blog on evidence-based running!

Is high fructose corn syrup eviler than table sugar?

No, but here is the long answer.

At least as far as your health is concerned, there is no difference. Politically and economically they are very different so you can decide there.

I'm posting this here because someone on letsrun.com innocently asked about the health of chocolate milk for recovery (which I think is a great source of carbs and protein) which quickly sunk into a HFCS bashing. Someone posted to the "proof" that HFCS is evil or at least eviler than table sugar (sucrose). That link is to a press report of a paper that got alot of attention earlier this year. I was moved enough to review the paper and write something to the letsrun message board. Here is my response, you may be interested

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The study referred to in this over-hyped press report is precisely why statistics in the hands of the ignorant creates the anti-science hysteria (anti-AGW, anti-evolution, anti-evidence based medicine) that is rampant on the internet. See also http://www.theatlantic.com/magazine/print/2010/11/lies-damned-lies-and-medical-science/8269

I will now use this paper in biostats 101 to test the ability of the students to find flaws in a published study. This will be an easy one.

Here are results (end point weight) from the first experiment

1. HFCS 24 hour + chow = 470 +- 7

2. HFCS 12 hour + chow = 502 g +- 11*

3. sucrose 12 hour + chow = 477 +- 9

4. chow only = 462 +- 12

First, why no sucrose 24 hour treatment?

Here is the take-home message from the authors and the press report:

1. the weight gain in the HFCS 12 hour treatment differs from the 12 hour sucrose treatment (no other differences found). Unfortunately, the authors do not actually give us the weight gains, only the table above. From the table we get the curious result that the final weight of the HFCS 24 hour treatment is actually LESS than the sucrose. if HFCS is so bad, why are these rats given 24 hours access to HFCS doing better than sucrose? The authors also do not account for multiple tests (type I error rate). Accounting for type I error rate, the statistical significance of the 12 hour HFCS v. sucrose disappears. Type I error rates is stats 101.

The authors did 2 other experiments, the "6 month" experiments, one on male rats and one on female rats. One of these didn't include a sucrose treatment so we can ignore that (interestingly, the entire paper is about sucrose v. HFCS so what is this even doing in the paper?). In the other, there is a reported difference between the 24 hour HFCS v. sucrose but not the 12 hour HFCS v. sucrose (just the reverse of experiment 1). Again, this reported difference disappears when accounting for type I error rate. What the authors failed to note at all was that the 12-hour HFCS weight gain was actually less than the 12-hour sucrose weight gain (of course this was not significant).

So what do the authors conclude in the discussion?

1. "In Experiment 1 (short-term study, 8 weeks), male rats with

access to HFCS drank less total volume and ingested fewer calories

in the form of HFCS (mean = 18.0 kcal) than the animals with

identical access to a sucrose solution (mean = 27.3 kcal), but the HFCS rats, never the less, became overweight. In these males, both

24-h and 12-h access to HFCS led to increased body weight."

Ah, no. There was no reported difference in the 24 HFCS v. 12 sucrose and even the 12 HFCS v. 12 sucrose is reported incorrectly. If you are going to make the claim that HFCS differs from sucrose, you have to explain why the HFCS 24 hour rats didn't differ.

"In Experiment 2 (long-term study, 6–7 months), HFCS caused an

increase in body weight greater than that of sucrose in both male

and female rats. This increase in body weight was accompanied by

an increase in fat accrual and circulating levels of TG, shows that this

increase in body weight is reflective of obesity."

Ah no. The authors didn't even look at the 6 month effects of sucrose in male rats so why do they make this claim? And there is no reported difference in the 12 hour HFCS v. 12 hour sucrose in females so how can they claim the difference. At least in this experiment the 24 hour results make sense, if it existed, which it doesn't.

There are numerous other smaller flaws that aren't worth bothering with given the major flaws in the design, the presentation, and the discussion. Was this paper even reviewed?

*****post script****

I posted this to LRC after someone asked the question:

thought i knew stats wrote:

Not doubting you, but would you mind elaborating what you mean by this? What are the "multiple tests", and how does the type I error rate compound?

---

That is a really good question. I left it out to keep the post from being too long. A type I error is a "false positive"; basically when the test is telling you there is a difference when in fact none exists.

In experiment one there were 4 treatments and so there are 4X3/2=6 ways to compare the different pairwise combinations (for example HFCS 12 hour v. HFCS 24 hour is one pairwise comparison). We don't have to compare all of these but in this case, all are of interest. So we have "multiple" tests (in this case 6. Whenever we have more than 1 test, the chance of finding a false positive (type I error) goes up (that is the chance of finding something improbable goes up if you go looking multiple times). In the case of 6 tests, our chance of finding a type I error goes from 5% (if that is what we want) to 25%. So there are very, very well known methods to control for this. Really, it is stats 101 and there are too many papers in the literature admonishing researchers when they don't deal with it. Psychology departments are known for rigorous statistics and any psychology professor at Princeton will be well versed in this. I will claim here that the last author is willfully ignoring it.

The paper actually has three experiments and a total of 6 + 6 + 3 = 15 pairwise tests that are all testing basically the same thing so I would even go further and make the claim that they should be accounting for 15 (and not just 6 tests), especially given the extraordinariness of the claim (see below). The probability of making at least one type I error with 15 tests is now 54%.

Extraordinary claims require extraordinary evidence. The authors are making the claim that .45 glucose + .55 fructose does not equal .5glucose + .5fructose. This would come as a surprise to most physiologists. It's close enough to an extraordinary claim that most physiologists would require extraordinary evidence to be convinced.

* the chance of finding something improbable. The probability of being dealt four cards of the same color is 0.5 * 0.5 * 0.5 * 0.5 = 6.25%, which is not very probable. But if you dealt yourself 4 cards 10 times in a row, the probability of one of these "hands of 4" being all the same color would be much higher than 6.25%. It's why we can win at solitaire. Sometimes.

Marathon Time Comparison chart

Marathon	Ascent (ft)	Net (ft)	Time	MDF
Baystate	430	-14	3:00:54	1.0051
Boston	578	-446	3:00:12	1.0012
Maine	947	-5	3:02:06	1.0117
Manchester City	1438	2	3:03:14	1.0181
MDI	1655	-7	3:03:52	1.0215
Sugarloaf	671	-567	3:00:07	1.0007

The above data are using my new Marathon Predictor calculator based on Greg Maclin's algorithm. The Marathon Difficulty Factor (MDF) is based on the elevation profile only, not turns (which matter) and altitude (which matters, but not going to affect the New England marathons).

Don't like my 3 hour example? Your expected pace for any of these marathons is simply pace*MDF where pace is your pace on a flat course. I've worked out an example using a 3 hour flat marathon above. If you've run one of these marathons and want to know what the expected pace on another is, your unknown pace is pace(known)*MDF(unknown)*MDF(known). Very simple!

As I showed in my previous post, expected pace and time are a function of the hills and this is where my calculator differs from Maclin's. First, I'm not sure where he got his elevation profiles but at least some I think were obtained with a barometric altimeter on his Polar Watch. I would think this would nail it but he has some odd stats that kinda hit you across the face when you stare at his chart. For example, his total gain for Manchester City is only 100 feet more than Baystate. Based on everything that I've read (mostly blogs but also estimates from the various online mapping sties) this must be far from accurate. Also note that Maclin has the net elevation gain/loss for the Boston Marathon as -378 feet but a good look at the elevation profile provided by the BAA shows this is closer to 450 feet. Marathonguide confirms this. Given these are the only three marathons that I've looked at closely (Baystate, Boston, Manchester City), I don't have as much confidence in Maclin's elevation profiles as I have in mine. One other difference between our algorithms is that I use a 0.01 mile window to compute grade and pace not a 0.1 mile window. Since I smooth my elevation profile, I'm not worried too much about overestimating the MDF and I'd rather not miss important peaks and troughs that can occur well away from the 0.1 mile marks.

Thanks to Jim's suggestion, my elevation data come from the USGS NED database based on gps positional data during marathon races for runners running about a 7 min/mile pace. That is, I substituted elevation data from NED for the gps/satellite data. I found the marathon data from the old motionbased.com site. The data are then smoothed using a cubic spline and a smoothing parameter of 2.51E-04. This smoothing parameter was chosen based on a very detailed comparison of each of the hills on the Maine Marathon smoothed elevation profile and the Google USGS topo map (since I'm familiar with this marathon, this proved fairly painless). I used the same smoothing parameter for the other marathons.

I've got a system now that I can very quickly compute these for any course that I have a gpx file so I'll add some more starting with those that are most relevant to New England.

A calculator for predicting marathon time based on elevation profile

Chuck pointed me to Greg Maclin's site and it's excel calculator for predicting marathon times as a function of hills and turns. I've now wasted 1.5 days building my own calculator in R based on hills only. R is a statistical programming language and I cannot compile it to make a web applet. Sorry.

Background info: Basically, every 0.05 miles, I compute a "pace adjuster coefficient" based on the grade of the terrain for that 0.05 mile segment. The pace adjuster coefficient is just the % increase or decrease in the expected pace on a flat course due to a hill. The formula for adjustment are from Maclin's xls predictor. Hills affect us more late in the race so the pace adjustment percentage increases for climbs but decreases for descents after mile 16 and even more after mile 21. The difficulty of a marathon (based on hills, at least) can be summarized with a single factor, which I'll call the Marathon Difficulty Factor, which is just the average pace adjuster coefficient over all segments.

The problem with any such calculator is the estimation of the elevation profile. Here are the total ascents (in feet) of 5 marathons using 4 different websites:

Marathon		Maclin	MMR	ARR	RA
Boston		544	295	897	1129
Maine		NA	427	955	1230
Manchester		629	758	NA	1742
Baystate		526	295	552	583
MDI		NA	659	1870	2252

MMR is mapmyrun, AAR is USATF's America's Running Routes, and RA is RunningAhead.

In general, the total ascent is ordered RA > USATF > Maclin > MMR but there are enough exceptions that no general rule can be created. More importantly, these differences have consequences on the calculated running time (and Marathon Difficulty Factor). Because I can manipulate the smoothing parameter of the spline that I fit to the elevation profile, my calculator can compute the expected time based on any of the above estimates. Cool huh?

So here is what I get for the Maine Marathon based on a 3:00:00 marathon on a flat course (MDF is the Marathon Difficulty Factor, which is the same for any goal time. Multiply the MDF to your flat-course pace and you've got your hilly-course pace!):

Ascent Time MDF

RA 1219 3:02:47 1.0154

ARR 955 3:02:10 1.0120

MMR 425 3:00:53 1.0050

So which am I to believe? At the bottom of this post, I've inserted an image of the three elevation profiles for the Maine Marathon based on the above three total ascents. Based on my knowledge of the course, the MMR profile is clearly too smoothed; it underestimates both the grade and peak elevation of the hills (that is, it flattens the hills out over a longer distance). The RA estimate looks to be not smoothed enough. And the USATF estimation looks about right.

Added at 6:16PM: MapMyRun ignores ascents less than 60 meters. Holy cow! Even the downloadable .csv files though seem to be oversmoothed relative to the other sites.

For my running bro' Jamie, here are the estimates for the MDI marathon

	Ascent	Time	MDF
RA	2112	3:04:57	1.0275
ARR	1857	3:04:20	1.0241
MMR	660	3:01:34	1.0087

Two notes:

1. I always wondered how much hills mattered. Is MDI 1 minute or 5 minutes or 10 minutes slower than Maine for a 3Hr Maine marathoner? Based on my initial results, I'm pleasantly surprised to find that something like MDI probably adds only 2 minutes on top of Maine. However, just like Mt. Washington, when things go wrong on hills, they can go very wrong. That is, if a hill is run too fast (the actual pace isn't adjusted by effort), a slow death spiral will surely result. So a well-run hilly marathon should be within 2-5 minutes of a well-run flat marathon but a poorly-run hilly marathon will be many, many minutes slower than a well-run flat marathon.

2. For the purpose of comparing MDF among marathons, what we really need is course elevation profiles collected and smoothed in the same way. Maybe all MMR or RA or USATF.

The RunningAhead elevation profile of the Maine Marathon. A little undersmoothed?

The USATF America's Running Routes profile of the Maine Marathon. About right?

The MapMyRun elevation profile of the Maine Marathon. Definitely over smoothed.

Fall (post-marathon) goals

1. win Wolfe's Neck 5K

2. win Pathfinder's 5K

3. sub37 at Great Osprey 10K

4. run in hell

1. row on erg

2. double pole on roller skis

3. look for snow

So true, Robbie

The best laid schemes of mice and men
Go often askew,
And leave us nothing but grief and pain,
For promised joy!

Physical Therapy

First, let me congratulate my running buddy Jamie Anderson for the BQ at the badass MDI marathon. Wooooohooooooooo! Sweet, we're going to Boston! I was very anxious last night and this morning and very glad that mad spectator Ryan was tweeting updates. I got the news at about the Freeport exits of I-295 (don't tell the state troopers!).

Training has gone well this season and I'm in the mood to race so I hope to jump in 3-5 races over the next few weeks, both XC and road. Unfortunately I trained for the marathon and have done no running faster than MP - 10s for about 8 weeks and prior to that my speedwork was only at 5K pace so this isn't the best prep for fast xc and road races. I also of course ran a marathon two weeks ago which itself is not good prep for fast xc and road races. So my Craig Cup last saturday was my first speedwork of the fall. I was hoping to do more speedwork Wednesday but my calves are shot from the perfect storm of marathon/craig cup/low heel shoes so I ran easy at Back Cove instead.

Physical Therapy 8K race report:

Today was my second speed workout and it was again a race - the Physical Therapy 8K in Brunswick. I had not run this race before but Floyd L., David R., and some other FODs have run this over the past few years so I was hoping to see them. The race is also free for MTC members so that sealed the decision. I punched 17:45 5K into MacMillan's calculator (which is 13 s faster than my PR but I feel good!) and got a goal time of 29:15 or 5:53/mile. I didn't see Floyd or David or any Dirigo masters but I did see Bob Ashby, who has some impressive marathon times. I also had a nice starting line chat with Mike Bunker who took my A&P class a few years ago and is a wicked fast former USM steepler. I took off at what I was hoping was 5:55ish and pretty quickly found myself alone in 5th place with a decent gap both in front and behind. It largely stayed this way for the rest of the race. I hit mile one in 5:56 and felt good. I hit mile two in 5:53, again good. I hit mile 3 in 5:56, again good but about 3s slower than I wanted. Very soon into mile four I caught and passed the fourth place runner. We had turned into a wind and I was hoping to share the pulling but he was hurting. Mile four is a slight hill - about 80 feet in 1/2 mile and it was against a slight wind. Both seemed pretty trivial but my mile 4 split was 6:07. Ouch, I was hurting throughout mile 4. Mile 5 was just brutal. I was slowly catching up to the 3rd place which was a woman that I didn't recognize. But I couldn't catch her. I was spent. Last .9x mile was at 5:59 pace. Finish time 29:42, 4th overall, 3rd male. Mike Bunker cruised in for an easy win and Bob Ashby cruised in for an easy 2nd place. The woman turned out to be a former Brown U. runner Jenna Krajewski. I was a teeny bit disappointed with my time. Its about 2-4s slower than my equivalent MD5K/B2B times but I was hoping to have gained speed since then. It was also much harder than my B2B - I was really hurting today but the B2B seemed so easy.

Physical Therapy:

I won a $50 gc to Soakology Foot Sanctuary and Tea House. Which is good because I need some physical therapy. I have both calf and lower back soreness and could use a good massage (not sure about the seaweed treatment though). My lower back mm. have been sore for about a month and last Friday was notable for being the first time that I've not run because of pain. After finishing up a meeting at USM, I was putting my backpack into the car and got a shooting pain in the lower back that felt very much like how my back felt when I played golf in high school. Yes golf really torques the back. Its not a continuous pain at all but a rapid, shooting pain that occurs when the back twists and bends just so (it's very hard to replicate consciously but not accidently). It happened again while driving over to Back Cove. At Back cove I took 2 steps and realized that each pounding foot fall hurt. So while I've taken rest days (and weeks and months) for fear of aggravating an injury, I've never actually not run because it was too painful until Friday. I tested it out with a little running in place yesterday and it felt fine but skipped the TMR SMR nonetheless. Today it was no problem. Hopefully a little soakology will put it to rest.