3 things I learned after training for and running a sub-3 hour marathon

Thursday, October 18, 2018. Author by Dr. Haran Sivapalan

Haran and his medal

Last Sunday I was lucky enough to travel to Germany to run the 2018 Munich Marathon. Almost 5,000 people lined up in the city’s Olympic Stadium, the venue of the 1972 Summer Olympic Games, to cover 26.2 miles (42 km) by foot. The previous 16 weeks had seen me running 4-5 times a week, doing core body workouts and adhering to a healthier diet than usual. My target was to achieve a sub-3 hour marathon, widely considered the holy grail of amateur runners across the world.

The first 18 miles of the race went according to plan, and I completed the first half in 1h:25m:50s. After mile 18, however, my legs started to cramp and the last 8 miles felt as if I was running through treacle. Nevertheless, I persevered at a slower pace and, to cut a 26.2-mile long story short, I just managed to hit my goal with only 23 seconds to spare. I eventually crossed the finish line in 2 hours 59 minutes 37 seconds.

While this feat is certainly not in the league of an elite athlete, it puts me in an exclusive club shared by only 2% of other marathon runners. More importantly, I feel I performed to the best of my potential and shaved almost 19 minutes off my previous personal best.

On that note, I thought I’d share some lessons I learned between my previous marathon in 2016 and my latest one in Munich.

 

Importance of nutrition

Unsurprisingly, marathon training involves running. Lots of it. This increased energy expenditure also meant I had to eat more calories, both to fuel my body for long distance runs and to promote growth and repair of my tissues afterwards.

The last time I was training for a marathon, I wasn’t particularly discerning about where my calories came from. I figured that I wouldn’t gain much weight if I was simultaneously burning lots of calories running. This led to me eating all sorts of junk, with excessive amounts of processed carbohydrates and saturated fat. Clearly, this was a mistake. Studies show that foods high in refined carbs, trans- and saturated fats can promote inflammation, lead to unhealthy fat deposition, cause crashes in energy levels and, ultimately, harm exercise performance and recovery.  

This time around, I made a concerted effort to eat more wholegrain, lower GI carbohydrates, which helped me to avoid rapid fluctuations in blood sugar levels. I also learned that hunger signals aren’t necessarily a reliable cue to eat more. In several instances, I had conflated hunger with thirst; and drinking more water helped to curb feelings of hunger. As a carrier of the FTO obesity risk allele, I also often found myself hungry mid-morning. Adding protein powder to my breakfast porridge allowed me to stave off cravings for unhealthy mid-morning snacks and also, as a vegetarian, was a useful means to help me hit my daily protein macro target.

 

Importance of recovery

It’s customary for marathon runners to taper their training for the last one to four weeks before a race. Tapering typically involves gradually reducing the intensity and duration/mileage of running, allowing the body to recover and develop the necessary neuromuscular adaptations for the marathon day itself.

The last time I tapered for a marathon, I spent several days lazing around, doing no exercise at all. This time around, I incorporated more active recovery days – instead of doing nothing, I did some gentle cycling and walking. There’s evidence that active recovery is better than passive recovery, as it improves blood flow and expedites the clearance of metabolites that build up during exercise. 

 

Importance of understanding your genes

Running encompasses everything from 100-meter sprints to multi-day ultra-marathon events. Regardless of training, people will naturally gravitate towards one side of this spectrum. Some people are natural sprinters, while others have a talent for long duration endurance events. A person’s proclivity towards a certain running distance is largely determined by their genes.

According to my FitnessGenes results, I am RR for the ACTN3 gene, which is useful for high-velocity muscle contractions involved in sprinting. I’m also AA for the MCT1 gene, which means that I’m likely to clear lactic acid more effectively after a high-intensity effort. From my personal experience, I much prefer speed work/ interval training sessions and running fast in short bouts. When training for previous marathons, I would largely perform shorter fast runs, as I was better at them and found them more enjoyable. In other words, I naturally gravitated towards these shorter distances.  The downside of this, however, is that I would neglect the slower, longer runs, where the emphasis is on training your body to run high mileages.

Knowing that you have certain strengths and weaknesses, based on your genes, can help you plan your training more effectively. As part of my training this time, I still did speed work, but I acknowledged that I would have to put more effort into my long runs.

Overall then, while the race didn’t go perfectly, I was pleased with my performance in Munich and feel that my FitnessGenes results helped me achieve that much-desired sub-3 hour marathon time!

Need help choosing a plan?

Use our Plan Advisor to determine which genetically tailored diet and exercise program best fits your needs.

Find out
Sign up

Newsletter sign up

Sign up to receive our FREE newsletter and emails featuring articles on genetics, exercise, nutrition, customer success stories, new product information and promotional offers.

You're signed up

Thanks for signing up to the FitnessGenes newsletter, we’ll keep you up to date with our latest news and offers.

Quick links for testing on stage

Some technical debug stuff

Location

X-Forward = 54.226.209.201:54284
Remote-Addr = 54.226.209.201
Your IP Address = 54.226.209.201
Override location = =>
Override pricetable = =>
Your Continent = NA - North America
Your Country = US - United States
Your State = VA - Virginia
Your City = 4744870 - Ashburn
Your Price Table = USD
Location comments =