I Am Not Average

In case it is not obvious, this is not a real ad. Photo from U.S. News and World Report.

[Part 3 of 3 in a series on whether I should give sprint workouts another try.]

The Problem

Since before my first blog post back in 2012, I have been trying to decide if sprint workouts, AKA brisk or high intensity workouts, would be beneficial for me. On the one hand, when I have introduced sprint workouts into my routine, I have not noticed a lot of benefit. Rather, I find that they frequently drive me into overtraining. On the other hand, everything I have ever read about training highly recommends them.

So what have I been reading? The first thing I started reading were training books written by cycling coaches. I have had a bipartite cycling career, the first part running from 1965 or so and continuing full force through 1970 and then slowly petering out until 1978 when it stopped completely. The second part started in 2008, stopped in 2009, started again in 2010, and has continued with ups and down but no significant breaks into the present. Even back in 1965-1970 when I was racing, I did not have a particularly organized training plan, I just rode from challenge to challenge. When I restarted cycling in 2008, I took the same approach. However, when I tried to train for a 200K (124 mile) brevet (challenge ride), I found it more difficult than expected, and my wife bought me "The Complete Book of Long-Distance Cycling" by Burke and Pavelka, where I first encountered the concept of an organized training plan. Following the plan in that book I successfully prepared for a 200K brevet in the spring of 2012. However, I quickly ran into problems and developed questions which lead me to read a variety of such books. I have found these books extremely helpful as a source of ideas, but my experience has been that some of those ideas seemed to work for me while others didn't. In retrospect, I think this was due to a fundamental limitations of such books. It seems to me that central to the concept of coaching is the interaction between coach and trainee. The coach tries workout ideas, sees how their trainee responds, and adjusts accordingly. This central interplay is, of course, missing from the book experience.

As I continued to explore the world of training advice, I encountered scientific studies that compared the virtues of different training plans. Coaching is based on intuition and experience. These studies are based on science, and as a retired scientist, I found that most enticing. There is a whole ecosystem around such studies: they are reported with varying degrees of inaccuracy by the popular press, they are summarized by scientific, medical, and government entities into guidelines and are one source of ideas that coaches use to develop suggestions for their trainees and to put into their books and articles and blog posts, all of which I read compulsively. In all cases, I try to go back to the original scientific publications and read them critically but with an open mind. To date, I have reviewed about ten different scientific studies on exercise on this blog. In part 1 of this series, I reviewed a scientific study that examined the benefits of sprint workouts for health in the elderly (e.g. me.) In part 2 of this series, I reviewed a scientific study that looked for correlations between training intensity and improvement in cycling performance. In the case of almost all of these studies, I seem to find something in them that makes me question their conclusions. Issues I have commented on to date include:

1. There are too few subjects in a study so the results are not statistically significant.

 

2. There are problems with the study design, things like changing more than one variable at a time, that make the results difficult to interpret.

 

3. The study is observational rather than experimental and as a result, cause and effect cannot be proven.

 

4. The study is a biomarker study and as a result, it is not clear that what I care about (e.g. health) is improved just because the biomarker (e.g. VO2peak) is improved.

 

5. The subjects are very different from me (younger, more athletic) making it unclear if the conclusions of the study apply to me.

I would like to invest a few more words on Issue #5 and focus on one way in which the participants in most studies differ from me: they start with subjects who are not currently exercising. In contrast, I have been cycling more or less continuously for well over a decade. Why do so many studies start with sedentary subjects? I have yet to read an explanation but I have my guesses. One guess is that someone who is not exercising and then starts will exhibit a large increase in fitness. Large effects are easier to study, making this choice attractive to the scientists conducting the study. A second guess is that being sedentary is a fairly uniform state, people who are not exercising at all are relatively similar one to another. If you did a study on people who are already exercising, it is likely that they will have different exercise schedules and thus will be starting from different places relative to their maximum fitness. Thus, the same exercise program would be a step up in difficulty for some, and a step down for others. Is this really a problem? Would we not expect that the exercise program that best helps someone get into shape would be the same that would help someone stay in shape? Maybe, but given the popularity of periodized training, I suspect most coaches would not agree. The training that is best at the beginning of the season when you first restart training is very different than the training that is best at the peak of the season, and I would expect that the training approach which is best when you first start cycling is different than what is best after you have been riding for a few years.

Finally, I would like to introduce one more related issue with almost every scientific study ever done on exercise:

6. Results from such studies are the values averaged across a number of subjects.

 

The problem with that that nobody is average, everyone is unique. I have posted a lot on this blog about individual variation. If everyone is different, does it make sense to do studies at all? If everyone is different, doesn't that mean that everyone just going to have to figure out the best exercise schedule for themselves? I actually don't think so, not from scratch. Although no two people are exactly alike, we do have a lot in common so that, though not perfect, studies comparing exercise protocols which report a average across multiple participants are way better than no study at all and I appreciate having such studies very much. Sure, I have to test their conclusions for myself, but knowing the average response to a particular training routine helps me know where to start. That said, I think it is possible to do such studies in a way that would make them even more useful. 

Aren't statistics necessary for helping to determine if the results of a study are real or are due to random chance? Yes they are, but there are different ways of applying statistics and how statistics are used needs to match what is trying to be accomplished. In the context of training for cycling, there are two sources of variability in performance. The first is day to day variability. For a variety of reasons, people have good days and bad days. Usually, that is not very interesting and it gets in the way of comparing different training programs. Imagine I want to determine if a polarized plan or a moderate intensity plan is better to help me prepare for a metric century. I do the polarized plan, ride a metric century, but as luck would have it, I have a bad day that day, so my speed is slow. For the next ride, I prepare using moderate intensity training. That day, I have a really good day, so my speed is fast. I conclude that moderate training is better for me, but this is a flawed conclusion, the random noise introduced by good days and bad days has obscured the true result. I need some way to average out those good days and bad days. The way most studies do this is by averaging the results of several different riders, some of whom are having good days and others having bad days. The problem with that approach is that there is a second source of variability, and that is person to person variability. Let me explain with one example. There is a great deal of anecdotal evidence that as one ages, one needs more recovery between hard rides. Imagine a study to determine the optimal number of rides per week; 3, 4, 5, or 6. Imagine the study groups contained a mixture of riders of different ages. If one looked at the older and the younger riders separately, one might find different optima, maybe 4 days a week for the older riders and 6 days a week for the younger, but if you average everyone together, one might find an average optimum of 5 days a week, optimal for neither group. One obvious way to deal with that particular problem is to subdivide the study groups into groups of similar riders; men vs. women, older vs. younger, serious vs. casual; those who have been riding a long time vs. beginners, and so forth. One problem with that approach is that studies become very large, they require lots of participants to cover all the different subgroups. Another problem which I consider to be even more serious is that I believe there are subgroups of riders who will give very different results in a study who cannot be easily identified, people who look the same but who differ genetically in ways that affect their response to exercise. The solution to that problem is described in the Wikipedia article on N of 1 trials. Rather than average the results of several subjects, one averages the results of several tests on the same subject. In principle, this allows a study to reduce the noise generated by good days and bad days but retain the information on person to person variability. This approach is not perfect either. In the first place, each subject is accumulating training, building up fatigue, and aging as the study progresses. In the second place, it requires very long studies to provide the time needed to test different exercise protocols on each of the subjects in a study. Ideally, a mixture of N of 1 protocols and more conventional protocols on well defined subgroups would complement each other, providing more information than either would alone. However, this only aggravates the problem of needing very large numbers of subjects and long study times.

A Proposed Solution

At long last that brings me to the picture at the top of this post. As a senior, I get a benefit from Medicare and my supplemental insurance plan called "silver sneakers", a free gym membership. Neither Medicare nor my insurance company provide this out of the goodness of their hearts, they provide it because if I exercise, I will be healthier and and as a result they will save money on my medical care. Might that be true for younger people as well? Might it save insurance companies money to encourage exercise by paying for gym membership even for younger customers? Medicare, though it does not cover these younger people, might decide that on top of whatever immediate improvement in health exercise provides to the young, exercise now will make them healthier later when they reach their 60s and begin to be covered by Medicare, and thus save Medicare money in the long run. For the purposes of this post, let's assume that one or both of these is true, and that as a result, a significant number of people become eligible for subsidized gym membership. A requirement of such a subsidy might be that participants agree that in return, they will participate in studies comparing different exercise protocols. This could be a small ask, such studies could be designed to have minimal impact on a participants training plans.

Full disclosure, I have not taken advantage of my Silver Sneakers benefit because my preferred exercise is cycling and the gyms that currently participate in Silver Sneakers don't particularly support cycling. What I have considered is working with Five Rings Cycling Center, an organization that provides coaching for a wide range of cyclists from serious racing cyclists to casual cyclists like me. If my plan to improve the usefulness of scientific studies on cycling were to happen, besides increasing the number of participants, Silver Sneakers would have to increase the range of providers to include groups like Five Rings. What would be the requirements for an organization to participate? First, that they provide a program that the medical community agrees improves health. I would expect that most coaching organizations would easily meet this requirement. Second, that they participate in the scientific study part of the program. A requirement for coaches employed as part of this plan is that they abide by government guidance in designing the plans for their clients. Is any of this at all likely? That is an interesting question, but one well beyond the scope of this post. The thought experiment which is the subject of this post is to imagine, if some of the current constraints were relaxed, how might scientific studies on the benefits of different kinds of exercise be improved. For the purposes of answering that question, assume that the expansion of Silver Sneakers proposed here happened. 

How would that impact scientific research on exercise in general and cycling in particular? Specifically, how would the above plan solve the six common problems with research studies outlined at the top of this post?

1. "There are too few subjects in a study so the results are not statistically significant." The number of potential subjects available to studies would be dramatically increased. My guess is that this problem would become a thing of the past.
2. "There are problems with the study design, things like changing more than one variable at a time, that make the results difficult to interpret." At first glance it might appear that this plan might not help with this problem, but in an organized system like the above there would be more opportunities for investigators to interact with each other which should improve the quality of studies and reduce problems with experimental design.
3. "The study is observational rather than experimental and as a result, cause and effect cannot be proven." Coaches would ask people to do one or another plan. Those that were unwilling would not be included in the study.
4. "The study is a biomarker study and as a result, it is not clear that health is improved just because a biomarker is." Because the studies would go on for a long time, actual health data could be obtained.
5. "The subjects are very different from those wanting to use the results of the study ...  studies start with sedentary subjects." With lots of subjects available, many more subgroups similar to many more users will be available.
6. "The results of almost all studies are reported as an average of a number of subjects." Because subjects are in long term, N of 1 protocols become possible.

Given that the proposed changes in Silver Sneakers has not happened, does this thought experiment have any value? I believe that it does. By clearly imagining what a more ideal study would look like, I feel I am better able to evaluate the studies that actually exist.

Cycling in a Time of COVID-19

A diagram of the SARS-CoV-2 virus, the causative agent of COVID-19 

I am interrupting my series on high intensity workouts for two reasons. 1) Along with virtually everyone else in the world, my life has been disrupted by the COVID-19 pandemic. That disruption has made it harder for me to finish the third and final post. 2) On the other hand, the impact of that disruption on my cycling is something about which I wanted to blog. Thus, I promise to finish that series "real soon now", but for now, I am interrupting it with a post about my experiences cycling during the pandemic.

As I have confessed many times on this blog, I am a card-carrying member of the medical establishment. The COVID-19 pandemic has sparked the same partisan debate as has virtually every other issue in our society and I am not going to be a part of that. I am committed to following the guidelines of the medical establishment, partisan debate or no, but I do confess that is easier said than done. In the first place, there are a multitude of voices speaking for the medical establishment and few of them are immune from partisan influence. Medical professionals have been fired by government officials for expressing their opinion on COVID-19. In the second place, there is a great deal the medical establishment does not yet know about COVID-19. Almost all their advice at this point is their best guess based on fragmentary data and a lot of it is just best practice and common sense behavior for any infectious disease (e.g. washing hands.) Under these circumstances there are going to be legitimate differences of opinion, especially when you get to rather peripheral issues like the wisdom of cycling during a pandemic, even the best of governments are going to disagree. In Spain and Italy, recreational cycling is banned entirely. Fortunately for me, my state (California) and local (San Mateo County) governments have taken a different view, they explicitly allow and even encourage recreational cycling, albeit with some restrictions. The official restrictions are that social distancing should be maintained while riding and that rides should be taken locally, within five miles of home.

I am very reluctant, as a follower of the medical establishment and as someone who tries to be a good citizen, to engage in behavior that is less strict than what is recommended, but I do occasionally use my best judgement to decide to be a bit more conservative than the official recommendations, for example, on social distancing. The official government position is that social distancing while cycling involves keeping a six foot distance from other cyclists. There have been controversial studies and common sense discussions arguing that six feet is too close, that because of the motion of a bicycle and the wind generated thereby, virus might spread much further than six feet behind a cyclist. Because I mostly ride by myself, it is easy for me to sidestep this controversy and simply continue that behavior. Perfection, is, of course, impossible, so when other cyclists pass me or on the very rare occasions when I pass another cyclist, I get closer to them than I would like but I comfort myself that this is all about probabilities, so the fact that such encounters are short lived minimizes their harm.

Because most people cannot go to work, the amount of recreational walking, running, and cycling has increased dramatically. Before the pandemic, I would rarely see a runner or a walker or another cyclist while riding and now I see many more, such that encounters with all three of these groups has become more common. This has impacted my choice of routes. The Bay Trail, a favorite of mine, is simply too crowded for my comfort these days.

Due to an abundance of caution, I initially limited my cycling to my immediate neighborhood. However, this got boring after a while so I undertook the somewhat laborious process of making a snapshot of Google Maps and drawing a circle with a scaled radius of five miles around my home and found that most of my usual rides fit within this constraint. As I was doing this, I was cursing my outdated programming skills, thinking how much easier this task would have been had I been able to automate it, and of course, almost immediately found that someone already had. There is at least one site that allows you to enter your address and the desired circle radius in miles and draws the relevant safe riding circle for you.

"But why risk cycling at all?" many voices on the Internet ask. "Why risk an accident that will increase the burden on an already overwhelmed medical system?" Many of these same voices were questioning cycling long before this pandemic, arguing the same safety issue, and my response also remains the same: the real risks of an accident are outweighed manyfold by the improvement in my health that results from cycling. Sure, this argument is true in the long run, but is it really true in the short run, in the midst of a pandemic? Well, my local governments think so, and so I am going with that. That said, I am trying to adjust the cost-benefit in the face of the short-run conditions. I am always a very cautious cyclist, but I am even more cautious now. And I am also trying to take things just a bit easier. Long term, occasionally pushing myself to exhaustion can be a good thing, but in the short term, such all out efforts temporarily suppress my immune system, so I am trying to cycle enough to stay healthy but putting off any big pushes until COVID-19 is under control.

Stay healthy, wash your hands, and socially distance. See you on the other side of the pandemic.

Polarized Training and Athletic Performance

A Hill Climb

Photo from Tavo Mx on Pinterest

[Part 2 of 3 in a series on whether I should give sprint workouts another try.]

Is Polarized Training Better for Improving Athletic Performance?

In my last post I wrote that I had seen no evidence that I would be either more or less healthy if I substituted sprint workouts for some of my moderate intensity cycling. Thus, from a health perspective, I should do sprint workouts or moderate intensity rides entirely determined by what I prefer. Although health is my most important reason for cycling, having fun is also a very important reason and I think I would have more fun if I could ride a bit faster because that would allow me to do more rides with my friends who, as it happens, are faster than I am. Might sprint workouts make me faster?

Polarized training is training done mostly at very low or very high intensity and minimizes riding at moderate intensity. In the context of this series of posts, a polarized training advocate would argue that I should replace some of my riding at moderate intensity with a mixture of sprint workouts and rides even easier than my moderate rides. Vermeire et al., Journal of Strength and Conditioning Research: September 06, 2019 is a paper about the effectiveness of polarized training at improving athletic performance. I am not an expert on exercise physiology so I don't know the names of the reputable journals in the field, but I do recognize the name of the publisher of this journal, Wolters Kluwer, allowing me to tentatively conclude this is a legitimate scientific publication. The journal's claim to be the Official Journal of the National Strength and Conditioning Association suggests it may be much better than that. On the other hand, a big barrier to my reviewing this paper is that to see the full paper I would have had to purchase the article, all I can see without paying is the abstract. Fortunately, there are things we can confidently learn from the abstract. This study looks as 11 recreational cyclists, not a large number. According to the Bicycling article about this paper, these cyclists "were just beginning spring training. All the riders were preparing for a hill climb in the Alps or Pyrenees." At the beginning of the study, athletes were tested for power output at aerobic threshold (a level of effort than can be maintained for many hours), power output at anaerobic threshold (a level of effort than can be maintained for 30 to 60 minutes) and the maximum power that can be generated going all out, an intensity that can be maintained for less than a minute. These athletes then trained on their own for 12 weeks following whatever training plan they liked, but during that training, the amount of time they spent exercising and their level of effort was recorded. At the end of the 12 weeks, the total training load (a combination of time and intensity) was calculated using several versions of the widely used TRIMP method and, in addition, the percent time they spent:
1) below the aerobic threshold,
2) between the aerobic and anaerobic threshold, and
3) above the aerobic threshold
...were determined. The power tests were repeated, and statistics used to determine if there were any correlations between how the cyclists trained and how much their power measures increased.

The first thing I note about this study is that it is both an observational study and a biomarker study*, and thus, as detailed below, has the limitations of both. The second thing I note is that the questions they chose to ask are not the ones I would choose. The first question they ask is if more training load (as determined by one of the TRIMP calculations) is better. Given the assertion that 65% of competitive cyclists train too hard`, I would assume not and don't consider this a particularly interesting question. The second question would, in principle, be more interesting, and that is does the percent of time spent training at different intensity levels matter? This is the polarized training question: is it better to train mostly at high and low intensity (polarized training), or mostly at moderate intensity? Because this is an observational study, that is, they allowed the athletes to train however they liked, their study contains two barriers to answering this question. First, the range of different training programs chosen by the subjects of the study might not cover the range of exercise plans that ought to be considered. What if none of these 11 particular athletes train in a particularly effective way? The second problem, common to observational studies, is that it is impossible to distinguish between cause and effect. Are the best athletes best because of how they train, or do they chose to train the way they do because of their natural athletic ability? It is very possible that athletes who are more gifted find intense training more enjoyable, but that the reason they perform better is not because of this intense training but due to their natural ability. Finally, there is the issue that this is a biomarker study, and more generally, that an exercise plan can only be judged with reference to its goal. The best training plan to win the Tour de France will be very different than the best training plan to win a gold metal in the Olympic 1000 meter individual sprint.

These reservations aside, what were the results of this study? Taking the results the authors reported in the abstract at face value, none of the TRIMP scores correlated with improvement in any of their three power measurements. However, when they fit an equation containing percent of training done at the three intensity levels to improvement in their power measurements, the power at anaerobic threshold was weakly but positively correlated (more is better) with training below aerobic threshold (easy training), was inversely correlated (less is better) with training between aerobic and anaerobic threshold (moderate intensity training) and strongly correlated (more is better) with training above anaerobic threshold (high intensity training, e.g. sprint workouts.) There were no correlations observed with power at aerobic threshold or maximum power. Thus, overall conclusion of this paper is that polarized training is better than moderate intensity training for increasing power at anaerobic threshold. At best, this is a conclusion limited to one parameter, power at anaerobic threshold, and it is left up to the reader to determine the application of that to their real world goals. Unfortunately, the other explanation for their data is that the best athletes who improve most from training prefer polarized training, that it is their ability, not how they train, that is responsible for their better results. Finally, this paper only includes 11 participants and they were free to choose their own training plans so may not have provided the best set of different amounts of high intensity training. That said, I liked the experimental design of looking at the correlation between amount of time spent at different intensities to various measures of fitness. I would be very interested in seeing a similar study done with many more participants and with a more structured set of training plans.

Does power at anaerobic threshold matter to me? Interestingly, after having given this considerable thought, I honestly don't know. I can't ride at anaerobic threshold for much more than 30 minutes and the rides I want to be faster on are metric centuries (62 miles long) and take me more like 300 minutes to complete so it might seem that power at anaerobic threshold would not be all that important. However, these centuries are not a single uniform effort. Rather, their effort varies over the course of the ride. My goal is to improve my ability to stay with my faster friends and maybe if I had more power for short bursts at anaerobic threshold I could stay with them under situations where I am now getting dropped, situations like heading up a hill or when the pace temporarily picks up, but who knows, and that's the problem with biomarker studies. Even if I were persuaded that polarized training would increase my power at anaerobic threshold (the biomarker) there is no way to know for sure if my ability to stay with my friends on a metric century ride will be improved.

I don't want to be negative about this paper, its limitations are due to the difficulties of doing exercise research, difficulties about which I have previously blogged. Sure, its results are far from definitive, but its experimental design is a clever response to the difficulties of these kinds of studies and I think that fairness demands recognizing that it is one more brick in the wall supporting polarized training, albeit a small one. Rather than criticizing this paper I would rather think about what it would take to get past the difficulties that plague this and other studies of exercise, and that is what I will do in the third and final installment in this series. Stay tuned.

---

* An observational study is one in which participants are not randomly assigned to different protocols (e.g. training plans) but rather chose their own training plan. They are observed, and those who chose one kind of plan are compared to those who chose a different kind of plan. The problem with observational studies is that the two groups are not "matched", those who chose one plan might be different on average than those to chose the other, affecting the results. At first glance this might seem like nit picking, but it is not, especially in exercise studies. People who are naturally more athletic will find it easier and more comfortable to exercise harder and will be overrepresented in the hard exercise groups. How much of their better performance is due to their harder training, and how much their athletic ability? On the other hand, in many cases an observational study is sometimes the only study one can do, an interventional study, where participants are randomly assigned to different protocols is just not possible for any of a variety of reasons. Observational studies ought not be dismissed, but they should be treated with more caution than an interventional study. 

   A biomarker study is one where what is measured is not the thing in which one is interested (e.g. the ability to race up a hill) but something easier to measure that is believed to be related, (e.g. power at anaerobic threshold.) The problem with biomarker studies is that the biomarker might not, in fact, be related to the thing in which one is interested.

` From an article by Coach John Hughes: "My friend and fellow cycling coach Neal Henderson says that 65% of the athletes he sees train too much, 25% train too little and 10% get it right – the pros who are paid to perform."

^ Quote by Thumper, in the Disney film "Bambi".

Reconsidering Sprints

[Part 1 of 3 in a series on whether I should give sprint workouts another try.]

I started looking at published training plans in about 2012, and from the beginning, I have been skeptical about the value of  sprint workouts (aka brisk training rides aka interval training aka high intensity interval training aka HIIT.) To understand why, consider one example from my recent past. At the end of last season (November 2019) my cycling ability was as good as it has been since I moved to California two and a half years ago. During the 8 to 10 months prior to that I did no sprint workouts. Just before that, about 9 to 10 months ago, my ability was as low as it had been since the move, and it was my impression that my low ability was the result of cumulative fatigue caused by the sprint workouts I had been doing back then. Why, given my many similar experiences, do I still think about giving sprint workouts one more try? Because the exercise community (e.g. the coach-authors*, including the one coach-author I still follow, Coach John Hughes) keep pushing them. But should I be ignoring this advice, as some of my readers have suggest, because it is meant for young racers, not for old fitness and recreation riders like me? Hughes is my favorite coach-author because he focuses on a wider range of cyclists than most, including older and less competitive cyclists like me. Recently, he published two articles (this one and that one) on roadbikerider about the value of interval training for two of his clients, 76 and 62 years old. To be fair, these are stronger. more competitive cyclists than I, but in his book "Anti-Aging: 12 Ways You Can Slow the Aging Process" Hughes also recommends high intensity training for older riders exercising for health. In that book, he claims that a recent scientific paper demonstrated that "intensity training increased the number of mitochondria where energy is produced but neither moderate cardio or strength training increased the number of mitochondria." I have previously noted that I was eager to review the paper from whence Hughes got this assertion and this post is that review. In summary, and with apologies to Coach Hughes, his statement is not supported by the paper he cites and explaining why gives me an opportunity to discuss some important principles useful for understanding a study like this.

Is High Intensity Interval Training Healthier than Moderate Intensity Continuous Training?

The paper I am discussing in this post is Robinson et al., 2017, Cell Metabolism 25, 581–592. The publisher of this paper is Cell Press, one I recognize from my years as a scientist as a highly prestigious publisher, and the study was done at the similarly prestigious Mayo Clinic, so I consider it likely to be a high quality paper. After reviewing it, I have no significant quarrels with the paper itself, but only with how Hughes interprets it. This paper does not attempt to compare the benefits of one exercise program to another, that is, it does not try to answer the question posed in the heading for this section. Rather, this paper is primarily about the changes in gene and protein expression underlying training effects. Because the primary goal of the paper was not to compare the benefits different exercise protocols, the experiments in the paper were not designed to that end. However, this paper does contain data that might speak to the issue, so we can look at it with that in mind, but need to do so with caution.

Two broad categories I use to classify scientific studies are:

1. Observational versus Interventional studies. Interventional are better, but not always possible.
2. Biomarker versus Actual Endpoint studies. Actual Endpoint are better, but not always possible.

This paper is interventional rather than observational (that is, it randomly assigns participants to different exercise protocols), so avoids the problems of an observational study, but it is a biomarker study and has the problems associated with that. Specifically, in this case, what we care about (the actual endpoint) is health, but it is almost impossible to measure that directly in an interventional study, so we study something we can measure that we believe is linked to health. The biomarkers used in this study are:

• VO2peak (a measure very similar to VO2max)
• Insulin Responsiveness (relevant to adult onset diabetes, for example)
• Muscle Mitochondrial Activity
• Fat Free Mass (Muscle Mass)
• Leg Strength

All five of these biomarkers are generally believed to be good indicators of health so in the interests of brevity I am going to assume that the results of this study are, in fact, relevant to health.

The overall design of this study was to compare four exercise protocols across two groups of participants, a young group (18-30 years old) and an older group (65-80 years old). None of the participants were exercising regularly before the study. This is a common but unfortunate precondition of many exercise studies. I will talk both about why this is common and why it is unfortunate in a later part of this series but will ignore it for this post. This is a fairly small study, each of the eight groups contains only 7 to 11 participants making the statistics of comparison between these groups pretty weak. As a result, only the largest effects can be seen and there is lots of possibility for both false positive and false negative results.

The four exercise protocols were a no exercise control group (SED for sedentary), a High Intensity Interval Training group (HIIT), a Resistance Training group (RT, e.g. weight training), and something they called combined training (CT) which was a mix of resistance and aerobic training. I am going to ignore the details of RT and the resistance part of CT. HIIT involved 5 sessions a week of aerobic exercise. The high intensity part was done 3 times a week and consisted of 4 intervals, each done for 4 minutes at an intensity of > 90% of VO2peak, with 3 minutes recovery between intervals. Converting 90% VO2peak to my training intensity levels, this would correspond to the border between Zone 5b and 5c. For me, this would be a very hard workout. The remaining 2 days a week were 45 minutes at a VO2peak of 70%, roughly equivalent to my MAF tests, an easy workout. The aerobic part of the CT protocol consisted of five days a week of 30 minutes at a VO2peak of 70%, like my MAF test only shorter. Because these protocols involve different intensities, to compare them would require a way to quantitate intensity, and there is no consensus in either the exercise or medical communities as to how to do that. (I have previously blogged about this issue.) That said, based on my intuition and experience I strongly believe that the HIIT protocol involves significantly more aerobic exercise than the CT protocol. Thus, there are three differences between HIIT and CT: the total amount of aerobic exercise, the distribution of that exercise across intensity levels, and the fact that CT includes resistance in addition to aerobic training. If the HIIT protocol were found to be better than the CT and RT protocols, it would not be possible to know if that was due to the greater amount of aerobic exercise in the HIIT protocol, the the higher intensity in the HIIT protocol, or the absence of resistance training in the HIIT protocol. These are very serious and realistic concerns, but having noted them, I will move on.

A lesson offered to virtually all scientists-in-training is "absence of proof is not proof of absence." This is particularly true in a statistical context. Traditionally, the scientific community has used a P value of 0.05 as the cutoff for statistical significance. This corresponds to a 1 in 20 chance that the difference observed is due to chance, or that you are 95% sure the difference is real. If you compare two things and the P value is less than 0.05, then you say the difference is significant. If the P value is greater than 0.05, then you say, not that there is no difference, but that the difference is not significant; that you have not demonstrated a difference. A difference may or may not exist, you simply cannot tell from the experiment you did. Because of the small number of subjects, this is a big issue for this study. Consider the assertion made by Hughes, that HIIT improved mitochondrial activity while CT did not. Here is the data from the paper that speaks to that assertion:

Increase in Muscle Mitochondrial Activity Resulting from Exercise

The dotted line at 0 is placed at the mitochondrial activity at the beginning of the study. If the value is the same as that after 12 weeks of study, then no improvement was observed. Each of the filled in squares or open circles represents the average improvement for the 7-11 participants after the 12 weeks of the protocol shown at the bottom of the graph. The result for each of the participants will be different, and that is how we estimate the variability in the results. Because of that variability, we are not certain that the average of these few participants gives us the exact value of how much each protocol improves mitochondrial activity, and this is shown by the lines above and below the average which give us the range in which we think the answer probably lies (with 95% certainty.) Those groups where the authors are at least 95% sure that mitochondrial activity improved are marked with asterisks. (More asterisks means less chance that the difference is due to chance, that we are more than 95% sure.) First note the SED group, the control group that didn't exercise at all. For both young and older participants, their average mitochondrial activity is lower than before the start of the 12 weeks, but that the difference is not statistically significant, we are not 95% sure that difference is real. In fact, we expect that it is not real, there is no reason for it to change in the absence of exercise. If we only look at the averages, then all three exercise protocols increased mitochondrial activity for both younger and older participants. However, in only three cases can we be 95% sure that is not just due to chance. Maybe RT helps, maybe not. Maybe older participants benefit from CT, maybe not. But now, compare each group not to where they started (the dotted line) but to each other. For example, compare the older HIIT and older CT groups. Although the authors of the study do not compare these two groups, we can estimate the difference by eye, and to my eye, the difference between them is not statistically significant. The difference that is observed is that the comparison between the mitochondrial activity in the HIIT group before and after they participated in the exercise protocol is statistically different, but that the difference in the CT group is not statistically different. I suspect that this is the basis for Hughes' assertion that HIIT improves mitochondrial activity and CT does not. If so, that is an incorrect conclusion from the data. The correct conclusion is that we have significance evidence that the HIIT protocol improves mitochondrial activity, but in the case of the CT group, it might improve mitochondrial activity or it might not, this experiment was not able to answer the question. In short, we cannot say that the HIIT protocol is better at improving mitochondrial activity in older participants than the CT protocol. Based on that, there is no justification for adding a sprint workout to my training.

Let's consider a second example:

Increase in VO2peak (maximum oxygen uptake) Resulting from Exercise

This graph looks at increases in VO2peak with exercise. VO2peak and the very similar VO2max are perhaps the most common biomarker used as a stand-in for the health benefits of exercise. These measure the maximum amount of oxygen a subject can use when exercising as hard as possible. Starting again with SED, the control group, we see the surprising yet statistically significant result that younger participants had their VO2peak decrease over 12 weeks. Despite the fact that this is statistically significant, absent some explanation for this result, I would be inclined to believe that is due to chance. After all, 95% sure is not 100% sure. When we look at the HIIT protocol, we see that younger participants seem to benefit more than older. To me, that says that sprint workouts might have been fine when I was young, but now that I am old, they might not be so helpful. In this case, the difference was so striking the authors calculated the probability that this difference was due to chance, and got a P value of 0.0037, meaning that they were more than 99% sure this didn't happen by chance. For young participants, the difference between HIIT and RT is even more striking; interval training (HIIT) is, with high probability, better than weight training (RT) for improving cardiovascular fitness. In fact, there is no evidence that RT helps cardiovascular fitness at all. (This is the result that would be predicted by both the scientific and exercise communities.) When we compare the benefits of HIIT and CT for younger participants, it looks to my eye to be on the very edge of significance, that we might be 95% sure that HIIT is better at improving CT for young participants. However, when we compare older participants, the average improvement for CT is greater than for HIIT, but but to my eye this difference is not statistically significant. That is, CT and HIIT are, as best we can tell, equally good at improving the cardiovascular fitness of older participants.

Conclusions

My conclusion after reading this paper is that it provides no evidence that sprint workouts improve the health of an older rider like me. Once again, absence of proof is not proof of absence, but if anything, the evidence in this paper suggests that sprint workouts provide no more or less benefit beyond what moderate intensity workouts provide, I should do sprint or moderate intensity workouts as I prefer. Why might I choose to do sprint workouts? First, because they take less time. I hate riding on a trainer, and when doing so, might prefer sprint workouts to get off the trainer as quickly as possible. Second, just because sprint workouts appear to offer me no health benefits doesn't mean that they might not help me become a better recreational cyclists. In my next post, I will ask if sprint workouts might be better than moderate intensity riding at helping me to increase my average speed on a ride, to help me keep up with my faster friends.

---

* I coined the term coach-author to help highlight the difference between working one on one with a coach and from taking advice from a book or article written by a coach. In the first case, I would refer to the coach as a coach. In the second case, I refer to the coach who is the author of the training book as a "coach-author". The reason this is important is if I were working with a good coach one on one, they would see how I responded to different training plans and would adjust their recommendations accordingly. In contrast, once a coach puts a training plan into a book or article, it becomes one size fits all, it might work for me or it might not.

Metric Century Progress Report

The Joy of a Group Ride
(The Great Western Bike Rally, 1968)

My first group ride after moving to California was the 2018 Art of Survival which I rode with my high school riding buddy, Roger. Back in 2016, at the Modesto Roadmen 50th Reunion, Roger urged me to ride Eroica California with him. I couldn't join him in 2017 because I was caring for my sick wife. When, in 2018, I again couldn't go with him, this time because I had pneumonia, Roger suggested the Art of Survival as another ride we could do together, and I managed to make that one. That event offered rides of various lengths, and Roger and I decided to ride the "metric century", a ride 100 kilometers (62 miles) long. The Art of Survival is held near to where Roger lives, a seven hour drive from where I live, so I spent both the night before and the night after this ride with Roger and his wife Janet and we had lots of time to talk about many things, one of which was Roger's plan to ride a metric century a month. I was very excited by Roger's plan, and decided that I, too, should try to do that, a plan I announced on this blog the following August.

Precisely what were Roger and I planning? Subsequent history indicates that Roger had a well thought out plan but I confess that my adoption of Roger's plan was an impulsive response to his enthusiasm and thus not carefully thought out. I think the reason I got excited is that I had really enjoyed the ride we had just done and wanted to keep doing rides like that. Upon reflection, there were two attractions of the Art of Survival ride that made me I want to do something similar on a regular basis: the social aspect and the challenge; I had found the ride hard but doable. Unlike the 200 kilometer rides I was doing five years ago, I hoped that I could do 100 kilometer rides without the months of preparation the 200 kilometer rides required, that they would not leave me so tired that it would be a year before I could do another one, and that I could do them on the hilly roads of California. And I also wanted to ride with Roger and with large groups of other cyclists.

When I got home, I started looking for more group metric centuries and built up a list of almost 100. The sources I used to assemble this list were the California Bike Ride Calendar and California Bike Rides. I took me some time to assemble this list, my babysitting responsibilities increased with the birth of my second grandchild, and as I worked my way through the list, I found that, for a variety of reasons (too expensive, too hard, ...) not all of them were rides I wanted to do. In fact, the first one I decided to try was The Golden Hills metric century in October. I mentioned it to Roger, he was interested, so we rode it together and had a great time. I also found that these group rides are not evenly distributed throughout the year. There were 17 rides in October, 1 in November, 0 in December, 0 in January, 1 in February,  and 2 in March, so all of a sudden, I was staring at April and Eroica California. The good news was that this year I finally made it to Eroica. The bad news is that the ride I chose was not a metric century. Why? Because the shortest ride at Eroica which qualified as a metric century was just too hard for me.

What made this ride "too hard?" As a general point, it is extremely difficult to come up with a route for a ride which is exactly 100 kilometers (62 miles) long, so a typical metric century is at least 100 kilometers long. Thus, at a given event, the shortest ride over 100 kilometers can be significantly longer than that. The shortest ride at Eroica was 33 miles long. The next shortest ride was 74 miles, more than the 62 miles of a metric century. But the problem with this ride was not so much the 12 extra miles as it was the hills. My 33 mile long ride included 1,400 feet of climbing. The metric centuries I have ridden have had about 2,000 feet of climbing. The 74 mile ride had 5,700 feet of climbing.

How much climbing is too much? During the 2019 season, I learned that I can ride 65 miles, I can climb 4,500 feet, but I probably can't do both on the same ride. The two metric centuries I rode were rated as "easy", but I still found them to be about as much as I wanted to do. They were each about 65 miles long and each had about 2,000 feet of climbing. In July of 2019, I rode a one pass version of The Death Ride which was 49 miles long with 4,500 feet of climbing, and I felt like that is was absolutely the hardest ride I can complete. One rule of thumb I have come across is that in terms of difficulty, is that 100 feet of climbing is equivalent to 1 mile of distance. If we add feet of climbing divided by 100 to distance to get a difficulty score, then the two metric centuries I rode each had scores of 85 and The Death Ride had a score of 94. Based on how hard I found the rides, that feels about right to me. The ride I did at Eroica had a difficulty score of 42, easier than I might have ideally chosen, but the next longer ride had a score of 130, more than I think I should attempt.

Another factor that affects ride difficulty is how fast the ride is ridden, not in absolute terms like miles per hour which is affected by things like how much climbing there is in the ride, but in relative terms, how hard I push during the ride. Consider my Go-To Alpine ride, 23 miles long with 1,300 feet of climbing which I have ridden approximately 100 times over the last two years. The fastest I have ever completed it is in 1 hour 44 minutes, the slowest, 2 hours 9 minutes. The fastest ride left me a lot more tired than the slowest. Despite my out of control compulsion for analysis and metrics, this is not an attempt to add one more parameter to my difficulty score but to recognize that such a score has its limits. This is just one example, there are many more factors that affect ride difficulty (e.g. choice of bike) but length and amount of climbing is where I stop.

At the top of this post, I noted that one of my major reasons for wanting to ride a metric century a month was because they provide opportunities to ride with my friend Roger. But even on my first ride with him, the 2018 Art of Survival, I realized he is a much stronger rider than I am. In contrast, he and his brother-in-law Dave, who ride together a lot, are similar in ability. For Eroica 2019, Roger and Dave did the 74 mile ride, while I did the 33 mile ride. For Golden Hills 2019, they did a full century (101 miles) while I did the metric (65 miles). Roger and Dave completed metric centuries each month from April through October of 2019, and they invited me along on all of them. In the end, I did Eroica, Art of Survival, and Golden Hills with them (albeit over easier routes in some cases.) Many of their other rides were too much for me, having up to 7,000 feet of climbing. As we were leaving Golden Hills this year to make our separate ways home, we shouted out "See you at Eroica!" I hope so, and I hope we see each other at Art of Survival and Golden Hills as well. That said, the reality is that they will want to do rides that are beyond my strength. As much as I would like to join their team, I don't qualify. What, then, should I do going forward? I don't need to ride metric centuries for my health, I can satisfy that need with much less riding, so I should do what is fun, and I think the social aspect more than the challenge might be the key to that. Right now, I am looking at the ride schedule of one of the local bike clubs, the Western Wheelers. Maybe riding with them is just what I am looking for.

Training

Wait, what, all of those posts on training for a metric century, that was all for nothing? Not at all! Even if I add no metric centuries to my schedule in 2020 beyond what I rode in 2019, I still need to get in shape for The Art of Survival in May and The Golden Hills in October. I have come up with two different approaches to being in shape for a metric century. The first is used when I have not ridden a metric century the previous month. It is the plan I used to prepare for the 2019 Golden Hills metric century. If I am routinely riding a 34 mile ride each week (which I am currently doing) it takes me 4 weeks to get ready for a metric century. The second training plan is to be used when I want to ride metric centuries two or more months in a row. Again, assuming I stick with my schedule of riding a 34 mile ride each week, then that is all the preparation I need. The only problem was that I had never tested that second plan, I had never ridden a metric century two or more months in a row. When I got home from Golden Hills in October, I executed my "metric century a month" training plans over the next 4 weeks and in November, I rode a solo 100 kilometer ride on local roads, and it went fine. I was tired at the end, but not overly so. A solo ride lacks the social aspect of the Metric Century a Month plan and is not a substitute for that, this was just a test, but a test I passed. Thus, the training plans I have blogged so much about should allow me to ride Group Metric Centuries whenever I want.

Bay Trail

Cover of the box containing the maps of the San Francisco Bay Trail

The San Francisco Bay Trail is a work in progress which has as its goal a Hike and Bike trail running completely around the San Francisco Bay. When completed, it is expected to be about 500 miles long. To date, 350 miles have been built and are available to ride. Who is building it? the Association of Bay Area Governments, known as ABAG, is organizing the effort. ABAG describes itself as "part regional planning agency and part local government service provider." ABAG was established in 1961 and in 1989, California State Senate bill 100 authorized them to begin development of the San Francisco Bay Trail. Although ABAG does the planning, the actual building of the trail is being done by the 47 governments along the route of this trail, all of which have agreed to be part of this project. These communities use the same process and funding sources to build the section of the trail going through their community as they would use for any other pedestrian or bicycle infrastructure.

When I heard about the San Francisco Bay Trail, I googled it and found its website. The first thing I looked for there was maps of the trails. There are maps online, but there are also paper maps for purchase, and I purchased a set of maps from the online store at the Oakland Museum of California. One concern with paper maps is they can quickly go out of date. This set of maps was copyrighted in 2016, so would appear to be at least 3 years old. So far, I have not encountered any discrepancy between the map and what I find out on the road, but I am sure I will as time goes by.

The map comes in the form of a deck of 24 4x7 inch cards, each card showing one section of the trail in high resolution. The cards are laid out around the bay as shown below:

So far, I have ridden two sections of this trail, one shown on Card 4, and one shown on Card 6. This is the section of the trail shown on Card 4:

Note that the start of the trail is purple, indicating a trail not part of the SF Bay Trail, in this case a very high quality bike and hike overpass over Highway 101. 101 is always difficult to cross so this overpass is much appreciated. The overpass leads directly onto the Bay Trail. The start of the ride is only 3 miles from my house, so the 20 miles of SF Bay Trail were the focus of the ride. This section of the trail is all paved and travels through heavily populated suburban parts of the Peninsula. I first rode it on July 4, and as expected, the trail was quite busy with bikers ranging from riders in full spandex on carbon road bikes to families with kids. Mixed with the bikers were joggers and walkers. It is definitely not the best place for an all-out training ride, but for a fun ramble, it works well. It is also not the best place to get away from civilization. The trail is 100% car free, but often runs next to roads so cars and houses and the other trappings of civilization are never out of sight. The trail runs through a number of popular parks which contributes to both the crowding and the charm. July 4 was windy this year, and I especially enjoyed the families flying kites. A final point important for setting expectations is that much of San Francisco Bay is more like a wetlands rather than a deep water port; frequently, the "bay" one is riding next to is mud rather than water, especially at low tide.

The section of the Bay Trail I rode that is covered on Card 6 is about 4 miles long and is 15 miles away from my home, so it is part of a longer ride rather than its focus:

Note that, once again, I started on a trail not part of the Bay Trail, the Stephens Creek Trail, a truly wonderful ride that I have mentioned here before. Despite being located near a very heavily populated part of the Peninsula, the trail itself is a bit separated from civilization, so riding has just a bit of a "getting back to nature" feel, though bridges and powerlines were never out of sight. The biggest difference between this and the section of trail I discussed above is that majority of this stretch of the trail is dirt/gravel rather than paved. Were it not for the map cards encouraging me, I might have wondered if me and my bicycle truly belonged, it looked more like a hiking than a biking path, but encouraged by my card, ride it I did. I rode this stretch of the SF Bay Trail on my Public Bike, an urban commuter, not a mountain or gravel bike, but it did just fine. The trails are quite smooth and reasonably firm. The biggest difference between the gravel and paved sections is that the gravel sections can have large mudpuddles, especially after a rain, so bikes do get dirty and fenders are much appreciated. How well these unpaved sections worked was a revelation for me. From now on, I will have no reluctance about riding the parts of the trail marked dirt/gravel.

I rode Card 4 and Card 6, what about Card 5? Much of the trail on Card 5 is drawn in dotted lines, indicating that it hasn't been constructed yet. There are alternative routes through much of this area, I have ridden on some of them, and it can be done, but it is not the seamless car-free experience that I describe above.

What's next? There is quite a bit of trail I have yet to ride connected to what I have already ridden, and I look forward to riding that, but ultimately, I am going to run into the dreaded dotted lines, gaps in the trail that remain to be filled. The metric that truly matters, in my opinion, is less the 350 of the 500 miles of trail have been built, but more how long the contiguous stretches of trail run, for that determines how long most people will ride before turning around and going home. That said, there are some stretches near where I live that make for a nice, car-free day ride. My older son his wife and I used to enjoy biking together, and now that they have kids, I would really enjoy taking them along. However, my daughter-in-law is not comfortable taking her kids into traffic on a bike. The San Francisco Bay Trail provides the perfect solution! All we need to do is to purchase and install bike seats, and a lovely car free day outdoors is ours.

Sad Surly Story

The Zombie, riding his cronenberged 1967 Hetchins Mountain King in the 2019 Gold Hills Metric Century

"It's springtime for Hetchins and vintage bikes, it's winter for Surly, so sad!" - To the tune of "Springtime for Hitler", apologies to "The Producers"

One thing I did not mention in my post about the 2019 Golden Hills Metric Century is that I rode it on my newly resurrected Hetchins. It wasn't supposed to be that way. Way back in 2018, in preparation for my first California metric century,  The Art of Survival, I decided I had neglected routine maintenance on my poor Surly Crosscheck for so long that I needed to do that ride on my Bianchi Volpe. Until then, the Surly had been my go-to bike,  the bike I rode unless there was some reason not to. After that, my Volpe became my go-to bike. Once I took care of the deferred maintenance on the Surly, my Volpe needed maintenance, so I swapped the Volpe for the Surly. This was a few weeks before the 2019 Golden Hills metric century and so the logical thing to have done was to ride Golden Hills on my newly overhauled Surly. But when I rode the Surly, I did not like the way it felt. So a plan was born, I would ride Golden Hills on the Hetchins, even though its gears were not as low as I would like, even though it had attachments for only one water bottle, even though I did not have a rack to carry the warm clothes I would need at the start of the ride.

How did the Hetchins do? It did great! As I have posted before, the lack of low gears on some of my bikes has turned out to be less of an issue than I initially feared, and once again, gears were not an issue on this ride. Some of the other potential issues which I mentioned earlier never materialized; the shift levers never slipped and the "soft" wheels held up fine. As for the lack of water bottle cage and rack, I figured out how to stash both warm clothes and a second water bottle in my jersey pockets. I have come to love the way the Hetchins rides and I continued to enjoy that during Golden Hills. Also, the Hetchins is a remarkable, vintage bike and I got to show it off. All and all, the decision to ride my Hetchins, initially forced on me by circumstance, turned out to be a huge win.

But what was wrong with the Surly? It had been my go-to bike nine years! Well, therein lies a story. It turned out that a lot of what I didn't like about my overhauled Surly was the saddle. I have come to prefer a well broken in Brooks B17 saddle so much so that I almost can't ride anything else. Unfortunately, I only have one of those and at the time my Surly came home from the bike shop, the it was in use on the Hetchins. I had a newer B17, less well broken in, that I put on the Surly, figuring it was close to being broken in and that it was about time to finish the job. So one problem was that the saddle was too hard. I made allowances for the hard saddle, but my intuition told me there was more wrong than that, and it turned out I was right. Another problem was not the saddle itself, but adjustment of the saddle. In my blog post "Saddles and Bike Fit" one adjustment I did not talk about was the tilt of the saddle, the extent the saddle is level, has the nose pointed up, or has the nose pointed down. I always thought that saddles should be level and I don't recall tilting of the saddle ever being an issue before. It was not that the saddle felt wrong on the Surly, it was that I felt like I had way to much weight on my handlebars. That was surprising, because weight on the handlebars is normally caused by low handlebars (relative to the saddle height), and my Surly has the highest handlebars of any of my bikes. When I thought about what else might cause that feeling, it occurred to me that if the nose of the saddle were too low, I might tend to slide forward, putting weight on the handlebars. When I looked back at the Hetchins, I noticed that the saddle was not quite level, the nose pointed up just a bit. Once I adjusted the tilt of the saddle on the Surly with the nose slightly up to match the Hetchins, the Surly became much more comfortable. (A number of cyclists on the Internet note that being more comfortable with the nose a bit up is yet another peculiarity of B17 saddles.) Had I figured this out sooner and/or if I had moved the broken-in B17 from the Hetchins to the Surly, I might have decided to take the Surly to Golden Hills, a decision that, in retrospect, would have been a lost opportunity to enjoy my Hetchins.

My Surly is much more comfortable now than when I brought it home from the shop, but I still prefer my Hetchins - by a lot! Why is that? Again, part of it might be the difference in saddles. The B17 on the Hetchins is well broken in, the one on the Surly still has a ways to go. If so, that should be a self correcting problem, and to that end, I am going out of my way to put miles on the Surly and its still-hard saddle as well as slathering that saddle with Brooks Proofide. However, I think there is more to it than the saddle. Back when I was in High School, the Modesto Roadmen had a belief that different bikes had different feels when ridden, some better, some worse, and that there was no way we could tell by looking at a bike how it would feel. I remember that we found that Raleigh bikes usually rode better than we expected, for example. As a scientist, I have to believe there is no magic to this, and as I have come to learn more about bicycles, I have learned some things that are less apparent but impact ride quality. One set of things, visible but perhaps not obvious, is frame geometry. Another which is entirely invisible to the naked eye but apparently has a big impact on ride quality is the kind of steel tubing used to make the frame; that tubing can be made from different grades of steel and the walls of that tubing can have different thicknesses. I think some of that is going on between the Hetchins and the Surly. Gebhardt at Veloro Cycles has suggested that wheels and tires might be a factor as well. The Hetchins feels quite lively, whereas by comparison, the Surly feels like a brick. This is not new. Although the Surly was my go-to bike for nine years, this was despite it having a bit of an unresponsive feel. Part of the reason this did not bother me more at the time was that the only bike I had to which I could compare it was my Bianchi Specialissima, and the fit of the Surly was so much better as to more than compensate for any difference in frame feel.

Seat firmness, width, and handlebar height

The not-yet-broken-in and thus hard B17 saddle may not be the only problem with my Surly, but it is definitely a problem. I have previously discussed how I position my saddle when adjusting my bikes. Another set of issues that arose while doing those experiments concerned seat width and firmness. Of course, choice of a saddle is a very personal decision, what works for one cyclist may not work for another. What I am going to talk about here is one cyclist (me) and the comfort of the same saddle on different bikes.

I am going to talk about four saddles and four bikes. The saddles are a well broken in leather Brooks B17 (old B17), a second B17 still in the process of being broken in (new B17), a synthetic Brooks C19, and the same saddle in a narrower width, a C17. The bikes are my 2010 Surly Cross Check (Surly), my 2007 Bianchi Volpe (Volpe), my heavily modified 1967 Hetchins Mountain King (Hetchins), and my 1960 Bianchi Specialissima (Specialissima). There are some small differences in the geometry of these bikes which might be relevant, but I have no hypotheses about those so will not be discussing them. What I will be discussing is the differences in the height of the handlebars relative to the height of the saddle on these four bikes. My working hypotheses are:

1. A softer, wider saddle can be more comfortable than a harder, narrower saddle.
2. A harder saddle can be comfortable if it is wider.
3. The lower the handlebars, the less weight will be on the saddle and the harder and narrower a saddle that can be comfortable.

None of my saddles are recommended for racing by their manufacturer, Brooks. The C19 is recommended for "Commuting .. in an upright riding position" (which is how I use it*.) The C17 is recommended for "City [and] travel ... hard riding in an angled riding position." The B17 is recommended for "Touring, Trekking and MTB (mountain biking)". The C19 is the widest saddle at 184 millimeters. Next are the two B17s at 175 millimeters. The narrowest is the C17 at 164 millimeters. Brooks advertises that the Cambium line to which the C19 and C17 belong do not require breaking in. I would rephrase that as cannot be broken in; both are much harder than a broken in B17. Using my fingers to judge, the newer B17 is the hardest of my saddles, the C17 and C19 are slightly softer, and the older B17 is clearly the softest.

My Specialissima has the lowest handlebars of the four bikes; they are 1⅜ inches lower than the saddle (low). Next is my Volpe with handlebars ¾ inches below the saddle (medium low). My Hetchins has handlebars 1¼ inches above the saddle (medium high), and my Surly has handlebars 2¼ inches above the saddle (high). I broke in my first B17 on my Specialissima with its low handlebars back in 2008, riding rides of up to 2 hours before the saddle was broken in with no bad consequences. In 2019, I rode the 2 hours of Eroica California on my Specialissima and the new B17 with no problem. When I recently put that same saddle on my Surly with its high handlebars and rode 34 miles on it, it felt very uncomfortable and I ended up with saddle sores. On the other hand, the old B17 feels good on all four bikes at any distance I have ridden, including a 10 hour ride on my Surly with its high handlebars. This suggests that low handlebars can make up for a hard saddle.

When I was first setting up my Hetchins (medium high handlebars) after its rebuild, I found that I could not correctly position a B17 saddle on it with the seatpost it had. I tested my C19 which I borrowed from my commuter and found that it could be positioned correctly, and that it felt comfortable during a 1 hour ride. Based on Brooks recommendations, I purchased a C17 for use on the Hetchins (returning the C19 to my commuter) but found that in a 1 hour ride is was less comfortable than the C19, and at the end of a 2 hour ride found it quite uncomfortable. This suggests that the reason the C17 is uncomfortable is a combination of being hard and being narrow. I borrowed a different seatpost so I could put my old B17 on the Hetchins and rode it that way for rides of up to 5 hours in perfect comfort. Noting that my Volpe had lower handlebars (medium low) than the Hetchins, I tried the C17 on it. It felt better in a 1 hour ride on the Volpe than the Hetchins, but not good enough that I would want to try it for longer rides. I then tried the C17 on the Specialissima (low handlebars), and found that it was comfortable for a 1 hour ride, confirming the hypothesis that a harder saddle can be comfortable when paired with lower handlebars.

How long does it take to break in a B17? The consensus of the community seems to be about 500 miles, but that is not my experience with the new B17. I have over 600 miles on it and it still feels much harder than my old B17 (which has well over 30,000 miles on it.) Is it possible that this is saddle to saddle variation rather than a lack of breaking in, that the new B17 will never be as comfortable as the old B17? Brooks leather saddles are known for such variability. Another possibility is that I waited too long to break in the new B17 - I purchased that saddle in 2012 and didn't complete my 500 mile break-in period until 2019. Only time will tell what the future holds for my new B17.

In summary, my experience, though certainly not a scientific study, did I support my hypotheses: a relatively hard C19 saddle is comfortable where an equally hard but narrower C17 is not. A not yet broken in B17 can be comfortable paired with low handlebars but not when paired with high handlebars. And a relatively wide, very soft, well broken in B17 will be comfortable on a wide variety of bikes. Using these parameters will help me pair the right saddle with the right bike depending on how I decide use them, but only time will tell how this will all play out.

---

* I purchased the C19 for a fifth bike, my Public commuting bike which has an upright geometry not easily comparable with the four road bikes considered here. This bike ought to put more of my weight on the saddle than any of my other bikes. That said, this saddle and bike combination are comfortable for up to 3 hours further suggesting that the C19 is a comfortable saddle, despite being hard.