Category Archives: Tracking

Race week meals – IM France

I already described my nutrition tapering on my blog previously, but have received quite a lot of questions regarding actual meals. I can understand that it can be quite difficult to measure the chosen amount of carbohydrates without proper food tracking (i.e. food weighting), so I decided to take pictures of all my meals in the entire race week.

But before going into the race week meals, I must also describe the carb intake in the preceding weeks:

  • 220 g of carbs per day in my hardest weeks of training before IM France (weeks -8 to -4),
  • 181 g of carbs in week -3
  • 159 g of carbs in week -2
  • 102 g of carbs in week -1 (i.e. last week before the race week).

This gradual reduction of carbs is consistent with reductions in training volume and further amplifies my reliance on fats for fuel.

On race week, I additionally reduced my carb intake to an average of 63 g before Friday’s dinner, when I usually start with a one and a half day carbo-loading protocol. But as mentioned in my race recap, that’s when I had a mild food poisoning with a tomato salad and boiled eggs. Almost immediately after I ate the salad, I had stomach discomfort, which lasted for three days. This resulted in limited food intake on Friday and Saturday. The plan was to eat in excess of 6.000 kCal on both days, but managed only 3.000 on Saturday! Well bellow of 5.700 kCal and 481 g of carbs as before IM Hawaii 2013 or 6.100 kCal and 435 g of carbs as before IM Lanzarote 2013.

On the following picture are presented all of my race week meals with times consumed.

B017 race week meals

And yes, those 4 pieces of pizza from the finish line probably contained gluten and I would not eat them if I didn’t suffered so much in the race. I immediately regretted it, as I felt even worse after eating them!

This week also concludes my 583-day tracking of food intake. I think that my kitchen scale deserves retirement!

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My blood lipid values

This is one of the most frequent questions I received since switching to Low Carb High Fat nutrition. It almost every time goes something in the line with “…your cholesterol must be off charts because of the high fat intake…” As it turns out, 2 common myths about heart disease are wrong, namely:

  • Eating cholesterol and saturated fat raises cholesterol levels in the blood.
  • High cholesterol in the blood is the cause of heart disease.

To argue against these two popular (and stubborn) myths is well out of this blogs scope, interested readers are therefore kindly referred to the works of i.e. Gary Taubes (Good Calories, Bad Calories), Robb Wolf (The Paleo Solution), Denise Minger (Death by Food Pyramid), Jimmy Moore (Cholesterol Clarity) or internet resources like blogs of Chriss Kressers, Denise Minger, Mark Sisson or Chris Masterjohn.

With some of common misconceptions out of the way, it’s also time for a disclaimer. I do not advocate measuring blood lipids, as they seem to be very poor indicators of general health. I perform these measurements manly because of curiosity and my geeky nature, as discussed many times before.

Unfortunately I don’t have any baseline lipid measurement directly before going LCHF, only some old results from regular check-ups in November 2010. After going LCHF in November 2012, I have measurements on roughly monthly basis for the first ¾ of the year and on roughly bimonthly basis thereafter.

My blood lipid values since going Low Carb High Fat (dots represent values from approx 2 years earlier, while on Low Fat High Carb)

My blood lipid values since going Low Carb High Fat (dots represent values from approx 2 years earlier, while on Low Fat High Carb)

One obvious remark that stands out of the diagram are elevated values of my total cholesterol in the first 6 months after going LCHF, mainly due to elevated LDL. But I do not worry about high LDL (or total cholesterol, for that matter), as with high HDL values and low triglycerides this is most certainly sign of elevated “large fluffy” LDL particles, that seem to be benign in cardiovascular disease. Unfortunately it would take quite a financial investment to confirm this thesis, but as stated before, I do not worry about it.

Besides having much higher HDL levels and lower blood triglycerides levels, my ratios of blood lipid values on LCHF are also much better, with all three relevant ratios in the Ideal range. Hence I sleep like a baby 😉

My ratios of blood lipid values since going Low Carb High Fat (dots represent values from approx 2 years earlier, while on Low Fat High Carb)

My ratios of blood lipid values since going Low Carb High Fat (dots represent values from approx 2 years earlier, while on Low Fat High Carb)

And if you are a bit of skeptic trying out LCHF yourself and you are worried about higher cholesterol levels, you can check out What to do if a Low-Carb Diet Raises Your Cholesterol.


Reference values:

  • Total cholesterol: 4,0 – 5,2 mmol/l
  • LDL: 2,0 – 3,5 mmol/l
  • HLD: >1,4 mmol/l
  • Triglycerides: 0,6 – 1,7 mmol/l
  • Total cholesterol / HDL ratio: preferably under 5,0 ideally under 3,5
  • HDL / LDL ratio: preferably over 0,3 ideally over 0,4
  • Triglycerides / HDL ratio: preferably under 4 ideally under 2
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Training Low

Carbohydrates are undisputedly ergogenic aids for endurance exercise training. There basically isn’t a single study out there that shows a negative effect of carbs on performance. So when going Low carb in training period, your training performance will suffer, either in volume, intensity or RPE (rating of perceived exertion). I finally managed to perform an analysis of my key training periods before Hawaii Ironman triathlon 2012 (High Carb) and before Hawaii 2013 (Low Carb), that confirmed my initial observations and findings from scientific literature.

I compared the last 14 weeks of training heading into Hawaii Ironman in 2012 or 2013 (three 4-week training blocks + 2-week taper), as this is considered the most important training period before Ironman race. In 2012 I was still on “traditional endurance” High Carb diet, in accordance with all guidelines and with no junk food. For 2013 season I changed to Low Carb nutrition at the start of the year, so the compared period in 2013 was well after adaptation to new nutrition (i.e. 8 months after the switch to Low Carb).

VOLUME COMPARISON

The first (and easiest) comparison is of course the volume of training, represented in km or hours.

B01101 Volume comparison

The numbers speak for themselves, as 11% reduction in total training time was hard to overlook even back when I was training for 2013 Hawaii. I averaged 3 h 03 min per day in 2012 and only 2 h 42 min per day in 2013. Only swim volume was greater in 2013, and that was due to broken ribs and arm lacerations in 2012, that limited my ability to swim. Both run (-18%) and bike (-18%) volumes were markedly lower in 2013, in accordance with previous observations, that I just couldn’t train that much. It wasn’t for the lack of time or motivation; it was just the volume that was killing me in 2013.

As far as the sleep goes, I averaged 9,0 hours of sleep per day in 2012 and 8,6 hours in 2013, so no major differences.

WORKOUT TYPE COMPARISON

The volume is only one determinant of training, with quality being probably more important. So the comparison of workout types may provide a better glimpse into changes between my 2012 and 2013 Hawaii preparation period.

B01102 workout type comparison

In running, I did a couple more interval training sessions and a couple of tempo and long distance workouts less in 2013 when compared with 2012. The major difference comes in other run workouts (i.e. recovery runs, “garbage miles”…), that I performed almost one third less in 2013! And the picture is almost identical for bike workouts in 2013, with the numbers of workout types quite similar except of “garbage miles” workouts (approx. one fourth less in 2013). So all in all, the quality of training was more or less comparable between 2012 and 2013, also confirming my initial feelings.

RPE, FATIGUE, WILLINGNESS TO TRAIN

As mentioned before, I also track Rating of perceived exertion, Fatigue and Willingness to train for every session. I assign a 0-9 value to each based on the following index:

Rating of perceived exertion Fatigue Willingness to train
1 – Very light
2
3 – Fairly light
4 – Moderate
5 – Somewhat hard
6 – Hard
7 – Very hard
8
9 – Maximum
1 – Feeling new
2
3 – Rested
4
5 – Average
6
7 – Tired
8
9 –Destroyed
1 – Very High
2
3 – High
4
5 – Average
6
7 – Low
8
9 – Zero

So another possible comparison between years could be based on RPE, Fatigue and Willingness to train criteria. RPE is excellent measure of how hard I went in each session (i.e. intensity) while Fatigue and Willingness to train are good indicators for overtraining status. By comparing these indicators for key workouts, I can get another view of the training quality.

I averaged these indicators for key workouts (i.e. interval, tempo or distance workouts) and for “garbage miles” workouts (i.e. all other).

B01103 RPE, FATIGUE, WILLINGNESS TO TRAIN

When looking through results, no difference appears in “garbage miles” workouts, whether they were run or bike workouts. This would indicate that intensity was the same as well as Fatigue level and Willingness to train. But when looking at averages from key workouts (i.e. intervals, tempos and distance sessions), the most notable difference is RPE, being quite higher in 2013 for both run and bike workouts. While on first thought this would indicate higher intensity and quality of key workouts in 2013, I would most probably ascribe that to typical characteristic of Low Carb training. Namely, for a given workout performed at lower muscle glycogen content (which is the case in Low Carb training) the RPE is higher at the same intensity or power. This fact is well established and proven in scientific literature, as subject always report higher RPE on Low Carb for the same workout intensity in comparison to High Carb.

Also, the track run workouts indicate the above mentioned fact of higher RPE at same pace as well. In 2012 I was performing 10x400m run repeats at 74 sec with average HR 150 bpm and 60 sec rest periods in between, while in 2013 I could only do 77 sec 10x400m repeats with average HR 150 bpm. But on 90 sec rests, so the overall intensity was substantially lower in 2013, albeit at higher RPE!

MY 2013 NUTRITION

Unfortunately, I do not have any nutrition data for the last 14 weeks before 2012 Hawaii when I was training High Carb Low Fat, but I would guesstimate that I was consuming well over 500 g of carbs per day. Probably more in 600 – 700 g region, as only my usual (cereal) breakfasts consisted of more than 200 g of carbs!

I started tracking my nutrition intake in 2013, so I have complete nutrition data for whole year. In last 14 weeks of training for Hawaii in 2013, my average daily carb intake was 199 g on 5.011 kCal consumption.

B01104 average nutrient intake

Average fat intake was 360 g, while protein at 231 g, which means that I got almost 2/3 of my energy from fat! As far as food groups goes, they averaged out as follows.

B01105 average food groups

CONCLUSION

Quite evidently, the most important training period (14 weeks before an Ironman) was lower in volume and at best similar with regards to quality in 2013 when compared to 2012. But as stated before, training performance is of minor importance with regards to race performance, as I train for races and not for training “bragging rights” 😉 The end result of different training approaches taken in 2012 and 2013 can be nicely summarized by the following graphic:

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

So where did this 38 minute (7%!) improvement come from? Some of it was evidently from better weather conditions, some were undoubtedly because of additional endurance training year, additional experiences… And I believe the major factor was also a change in nutrition. As far as I experienced until now, the Train Low Race High approach with regards to carbs has two major advantages:

  • Smaller reliance on carbs for fuel and correspondingly greater fat burning capacity, which means lower chances of bonking.
  • Greater training adaptation at lower (or the same) training stimulus (i.e. intensity and volume).

Especially the second advantage is most often overlooked and seldom mentioned. This may also be the consequence of quite limited research on this topic, as you can basically count studies that deal with this question on the fingers of one hand! But sadly, this advantage is in my opinion also one of major reasons, why people don’t stick with Low Carb training approach. They only see the reduction in performance in training, get scared and conclude that they are not suited to Low Carb.

In my opinion, based on my experiences gather so far and with regards to studied scientific literature, I could compare Train Low Race High Carb approach to altitude training. You are training at tougher conditions (higher altitude or lower muscle glycogen content) so that the races seem easier (sea level altitude or full muscle glycogen)!

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How I track my training

On 5th February 2000 I ran 3,7 km in the time of 15:45. This was my first entry into training log, which was in paper back then. 3.757 workouts later (until 2014) I get very nostalgic when holding those couple of papers that were my training log at that time. Now in the electronic age, I cannot hold my training log anymore as it is stored in a cloud. Being data geek, this is how I track my workouts.

My training log is of course in a form of Excel spreadsheet. The data entry sheet for specific year is arranged in rows, so that each row represents a date in a year. For each day I record the following things:

  • run training,
  • swim training,
  • bike training,
  • strength training,
  • In which part of the day workouts were performed (i.e. morning, AM, PM, evening),
  • weight,
  • and hours of sleep.

B00701 Daily data entry

For running sessions I firstly assign a label for the workout type, so that I can easily determine the intervals sessions, tempo sessions and long runs. Before the session numbers comes a brief description of the workout, while the numbers present duration, length, vertical gain, average and max HR and calories burned (as calculated by Polar watch).

B0070101 Run

Then I have 3 categories that present my Rating of perceived exertion, Fatigue and Willingness to train for that session. I assign a 0-9 value to each based on the following index:

Rating of perceived exertion Fatigue Willingness to train
1 – Very light
2
3 – Fairly light
4 – Moderate
5 – Somewhat hard
6 – Hard
7 – Very hard
8
9 – Maximum
1 – Feeling new
2
3 – Rested
4
5 – Average
6
7 – Tired
8
9 –Destroyed
1 – Very High
2
3 – High
4
5 – Average
6
7 – Low
8
9 – Zero

This allows me to assess my training / overtraining status. Furthermore, I also track in which running shoes I ran. The workout tempo and TSS (my Training Stress Score, more on that in a later post) are calculated automatically, and the yearly summary sits on the top of workout list.

I track swim training very unclearly, as I still haven’t found a suitable way to easily browse through main sets in a sea of drills. So I describe each workout in a list manner, then I note training duration and the total swim distance. I also note RPE, Fatigue and Willingness to train for that session and weather the swim was done in wetsuit.

B0070102 Swim

As with running, I first assign a label for workout type when logging cycling session. Then duration, distance, vertical climb, cadence, average power, HR and calories come, along with RPE, Fatigue and Willingness to train. At the end comes the notion of which bike, wheel set, tire and cycling shoes were used.

B0070103 Bike

I also track the type and reps / sets of strength exercises and their total duration.

B0070104 Strenght

On this sheet I also have some basic statistics of workouts I performed in the last week, month or in last specified days (i.e. number of workout, duration of workouts…). Beside this summary table is one very annoying cell, that shows me how many hours I am behind (or above) the planned weekly hours, which I have set at 21. If the cell is white, than I am on plan (at least based on duration), and if it is red, then I have some training to do.

B0070105 summary

This sheet in a workbook represents the data entry point, while I have some computed statistics on other sheets. They are weekly, monthly and yearly view sheets, which show weekly, monthly and yearly summaries.

B00702 Weekly view

B00703 Monthly view

B00704 Yearly view

I also have two other sheets, which show my cumulative yearly data for run / bike / swim volumes and run / bike / swim volumes in chosen time periods (i.e. in 30 days).

B00706 Cummulative view

B00705 Period view

Other various sheets include a list of all my races (122 up to this day), list and description of all my injuries, list of all my triathlon expenses, list of all my run track sessions and bike hill workouts and a list for yearly planning of training and races.

B00707 Races summary

B00708 Equipment summary

I find Excel really excellent program for my tracking purposes as it enables me any statistical analysis I choose. Over the last 10 year that I am using Excel, I updated this file gradually, adding various statistics and features along with some fancy formatting touches. This is the main reason for not using online programs like Garmin Connect or Strava as they limit me either in their statistics or at their presentation of the data.

I made a simplified version of my Excel spreadsheet for tracking triathlon training. Feel free to download and use it, if you find it useful!

Download “Training log” Training-log.xlsx – Downloaded 648 times – 257 KB

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Tracking body composition changes

Human body is composed of several materials, some of which are muscle, fat, bone, blood, urine… So measuring or tracking changes in body composition with weight scale is pretty much like observing total points scored in basketball games – 153 baskets scored doesn’t tell you who won and by how much! And when you factor also gut contents, gut microbioma (over 1kg in adults!), glycogen content (with all bound water), urine volume, hydration status… into body weight, the picture becomes quite messy.

Body fat caliper

Body fat caliper

So while I do track my body weight on daily basis (I am data geek, who thinks that even bad data is better than no data at all!), I now mostly rely on body fat measurements with skin caliper to track my body composition changes. The skinfold estimation method is based on measuring the skinfolds at several standardized body points to determine the subcutaneous fat layer. These measurements can then be converted into estimated body fat percentage by various equations. Although this method may not give you an accurate reading of real body fat percentage, it is very useful for tracking composition changes over a period of time. I mainly compare the skinfolds values (individual or the sum of values) over time and do not pay much regards to the estimated body fat percentage. All in all, the main goal is to reduce the subcutaneous body fat, so why not measure it directly!

The calipers are very cheap; you can even get electronic calipers for very reasonable prices! As previously described, I use mechanical caliper on 10 body locations (Chest, Abdominal, Thigh, Bicep, Tricep, Subscapular, Suprailiac, Lower Back, Calf and Midaxillary).

Skinfold measuring sites

Skinfold measuring sites

I made Excel spreadsheet for tracking my skinfolds, with body fat estimates from various equations from literature. The formulas used are from Parillo (9 sites), Jackson Pollock (7 sites), Jackson Pollock (4 sites), Ball (7 sites for general population), Faulkner (4 sites for athletes) and Wilmore (7 sites for athletes). But as stated earlier, I mainly check the skinfolds values.

On the next graph are represented my values from July 2013, when I started using caliper. I had average skinfold of 5 mm, and at just above 71 kg body weight the formulas estimated my body fat percentage to be in the range of just over 7%. Going into my A race of the year, Hawaii in October, I had a racing weight between 71 and 72 kg with 3,4 mm average skinfold (around 5,5% body fat). In my offseason (November, December) I gained back some weight to just over 75 kg and my average skinfold increased to just over 5mm. This indicates that most of my weight gain was due to muscle mass gain, in the range of 2 – 3 kg. Naturally, I also gained approx. 1 kg of body fat, mostly for insulation purposes 🙂 The increase in weight is intentional, as I am emphasizing strength work in this training period by performing a lot of leg and upper body strength work along with core strength exercises. The underlying reason is to build a solid foundation for demanding training sessions that will come later in the season.

My skinfold data with average body weight (red line) and average skinfold (green line)

My skinfold data with average body weight (red line) and average skinfold (green line)

So to summarize, I think the caliper is superior tool in comparison to weight scales for tracking body composition changes and far more useful in daily practice. That is if you are quite ambitious athlete, and need to lose only couple kg of body fat for that optimal race performance. When I will return to “normal” life without racing ambitions, I will gladly ditch the use of both weight scale and caliper and replace them with another proficient measuring device: my eyes!

So if you are an ambitious athlete, you can download my Excel spreadsheet for tracking body composition changes here:

Download “Body composition tracking spreadsheet” Body-Composition-Tracking.xlsx – Downloaded 1438 times – 69 KB

 

And  here are the preprinted notes for easier measurements:

Download “Skinfold measurement” Skinfold-measurement.doc – Downloaded 724 times – 509 KB

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Year in review – Training & Racing

I recently got reminded that the year 2013 ended and that it would be appropriate to publish also training data summary for the year, not just nutrition data. I basically do not view 1st of January as the start of season marker, as my 2014 season already started back in December 2013. But minor details aside, here are the summary data for 2013 season in comparison with all previous seasons.

My yearly totals

My yearly totals

The season 2013 could be summarized in one number as: -10%. That was my reduction in total training time. The reduction in training volume was highest at running (-18%) and was a consequence of my early season injury (raptured Achilles tendon in January). I was unable to run for 3 weeks, but recovered quite well after that, thanks also to excellent treatment of Tina Maze’s personal physiotherapist Nežka Poljanšek. Even though I increased my bike training at that period, my total bike training time fell by 8% in comparison to 2012. Swimming was more consistent this year, only 2% reduction in training time. I also did less strength work, -12% with regards to 2012. All in all, that corresponded to approx. 106 hours less training in 2013.

As far as the quality of training goes, I would rate it the same as in 2012, at best. My training performance was quite lower this year due to “Train low Race high” carbohydrate approach, as I’ve written previously. Not that I care, as the race results this year were markedly better, with AG win at Ironman Lanzarote (9th overall) and 2nd place AG (29th overall) in Ironman World Championship Hawaii. Even though the slower training times are a bit hard to swallow, the race times are what really count for me. This year in Hawaii I managed half hour faster bike split and went 5 minutes faster on the run for a sub 3h marathon!

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Comparison of 2012 and 2013 Ironman Hawaii race performances (2013 was Train low Race high Carb approach)

Injury wise, 2013 was much kinder to me. Beside above mentioned Achilles injury, I only experienced 3 episodes of diarrheas and one instance of eye inflammation. When looking through the 2012 list, which consists of broken ribs, arm lacerations, sciatica pain, shin splints on both legs, multiple occasions of ear infections, couple of diarrheas, lower leg muscle strains…, I would say that 2013 was relatively injury free 🙂

So what so conclude of 2013? It was my best triathlon season so far, as everything from training, nutrition and race performance fell almost perfectly together. My new Low Carb nutrition approach was the major breakthrough for me in 2013, as I managed to implement it successfully in training and recovery. Consequently, my general well-being was better than in previous years, which resulted in optimal foundations for great race performance. The 2nd place in AG at Hawaiian Ironman was therefore confirmation of the correct approach and hard work.

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Grocery list

A couple of months ago I stumbled on this interesting link that portrays grocery lists of 20 families around the world. While one could certainly argue the representativeness of pictures, I still believe that some rough estimates can be made from them. This inspired me to take my own “grocery list” picture, but realization is somewhat different from the original one. Firstly, it would be difficult for me to buy a whole week food supplies in one go and I buy a lot of items for longer periods (i.e. nuts, as they are cheaper in bulk quantities). I also buy some supplies in larger quantities, such as meat, and store them in freezer, so that all messy packing is done once a month. And finally, my apartment is small, so even if I gathered all items I could place them to fit in one picture. So the obvious solution is to take more pictures!

Vegetables and fruits

Vegetables

Vegetables

I buy most of my vegetables and fruits in local grocery store and recently more often in nearby farmers market. I try to buy local produce but I do not buy organic. In season, I also get quite a lot of vegetables from acquaintances living in Ljubljana suburbs.

Meats

Minced beef meat, beef liver, smoked pork neck, turkey fillet

Minced beef meat, beef liver, smoked pork neck, turkey fillet

I buy meat at butcher, with all meat from local stock farmer. As with vegetables, I also get quite a lot of meat (especially beef liver!) from small local farmers in Ljubljana suburbs.

Milk and dairy products, eggs

Dairy products (cottage cheese, sweet and sour cream, butter) and eggs

Dairy products (cottage cheese, sweet and sour cream, butter) and eggs

Luckily, we have a “milk-o-mat” just under our apartment building. Every morning, a farmer from Ljubljana suburbs delivers freshly milked (raw and full fat) milk, which you can then pour into your own containers. I use glass bottles, and the milk lasts 3 days in the refrigerator. Lately, I also get most of my cottage cheese, cream and sour cream from small local farmers. Taste of local milk and dairy products is really worth extra effort for obtaining them. And to keep me busy, I also experiment and quite frequently make my own cottage cheese, but more about that in some later blog post.

As far as the eggs goes, I try to buy them from local farmers as well, as you can really taste the difference from the battery cage farms eggs.

Nuts and seeds

Brazil nuts, Hazelnuts, Almonds, Walnuts and Macadamia nuts

Brazil nuts, Hazelnuts, Almonds, Walnuts and Macadamia nuts

I buy nuts in large quantities (kilograms!) in market places or in local grocery store. I keep them in glass container, as (I learned that) moths can easily infiltrate into plastic bags!

Fishes

Tuna, salmon and sardine cans, hake, salmon and tuna fillet

Tuna, salmon and sardine cans, hake, salmon and tuna fillet

I buy sardines, tuna and salmon in cans or tuna and salmon in fish market. I use cans for salad snacks at workplace or at home, while fish steaks are usually for lunch. When buying cans, I only buy if fishes in olive oil or in plain water. Absolutely no vegetable oils!

Weekly Totals

Based on my nutrient intake counting, as described in one of my earlier posts, my average weekly totals for 2013 add up to:

  • Milk – 2,97 l,
  • Dairy products – 4,79 kg,
  • Meat – 1,99 kg,
  • Fish – 0,91 kg,
  • Fruits – 1,91 kg,
  • Vegetables – 6,09 kg,
  • Eggs – 0,87 kg (approx 14 pcs),
  • Nuts & seeds – 0,64 kg.

These weekly totals represent quantities only for me. Frequently, I also have to feed another endurance athlete 😉 She eats mostly the same meals as me, so the weekly totals for my household are quite larger. Occasionally I do have to feed my daughter Ajda as well, but it seems that the later doesn’t eat much of what I cook 😉 So I would deem her effect on weekly totals as negligible…

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Year in review: my nutrient intake

25.11.2012 – 25.11.2013

I had a 1 year Low Carb anniversary on the 25th of November. The year went by really fast and as the 2013 comes to an end, it’s time for some housekeeping. As mentioned in my previous post I track everything I eat on daily basis which enables me some nice analyses. I summed my nutrient intake for a year (365 days), and got some interesting results.

My average daily energy source from macro-nutrients

My average daily energy source from macro-nutrients

All in all I ingested 1.7 million kCal, with 69% coming from fat, 18% from protein and remaining 13% from carbs. That is 132 kg of fat, 77 kg of protein and 52 kg of carbohydrates (enough energy to heat water in a 1,4 m deep 50 m swimming pool for 1 °C !).  On average daily basis that equates to just over 4700 kCal per day and 360 g of fat per day, 210 g of protein and 143 g of carbs.

My average daily intake of macro-nutrients

My average daily intake of macro-nutrients

As far as nutrient groups goes, the vegetables are the most prevalent by weight in my nutrition, with approx. 870 g per day. Dairy products (685 g per day) and milk (424 g) follow, while on average I eat 284 g of meat and 130 g of fish per day. I also eat 273 g of fruit on average per day. All of that food then totals to some impressive yearly amounts: 317 kg of vegetables, 100 kg of fruit, 104 kg of meat, 48 kg of fishes, 250 kg of dairy products and 155 liters of milk.

My yearly average of various food group intake per day

My yearly average of various food group intake per day

Energy wise, I spend on average approx. 1680 kCal per day swimming, biking or running. With consuming 4700 kCal per day that means my current basal metabolic rate is around 3000 kCal, as my weight remained approx. the same.

Are there any other analyses you would like to see?

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Tracking nutrient intake

This is one of the most frequent questions I received since starting this blog. It’s really quite simple, it only takes few ounces of effort per day for benefits that are quite substantial and greatly outweigh the extra labor. As of now, I have a complete list of everything I ate from 25th of November 2012, which is over a year worth of nutrition data. When this information is coupled with my training dairy, I can really evaluate the impact of nutrition on my performance and recovery, body composition and body weight…

Basically everything you need for successful nutrient tracking is a kitchen scale and spreadsheet application. And a bit of tips & tricks to minimize the time consumption. But first, the #1 used appliance in my home:

Kitchen scale

Kitchen scale, pre-printed paper note, pencil. And 190g tomato (5g carbs, 2g protein, 0g fat, 34 kCal)

Kitchen scale, pre-printed paper note, pencil. And 190g tomato (5g carbs, 2g protein, 0g fat, 34 kCal)

Nothing fancy, approx. €15 investment with a great cost-effectiveness ratio. Digital is of course better and besides, it’s harder to get analogue scale anyway. Just be prepared to change batteries often 😉

Being the most used item in my kitchen, it stands in the middle of my kitchen counter, so it is no problem to scale everything that goes into the dishes or directly into my mouth. Somewhere near are also a pencil and a block of paper for writing down the qualitative and quantitative composition of meals. This is the time for a tip that I foundnd very useful. I preprint small notes with usual foods I eat for breakfasts, snacks or launches, so when I weight things, I only need to put down the quantity. It might not seem much of an improvement, but when you think how many “macadamia”, “cottage cheese” and other long words it saves, it’s a big time saver on a cumulative scale. Along with food items and quantities I also note the time of meal consumption.

Although I eat vast majority of my meals are at home, there are inevitably some situations that prevent me the use of my kitchen scale, i.e. dinning out situations. The composition of those meals is of course less accurate, due to estimation quantities, but when you weight your every food for about a week, you quickly get a hang of quantities remarkably accurately. Let alone if you weight your food for a couple of months, this estimation is really no problem at all. I often even “play” with my assessment capabilities in the kitchen, estimating the weight of items before actually weighting them. And surprisingly, I am not far away in estimates for the items that I use the most.

Spreadsheet application

As described before in my blog, I developed my own spreadsheet for tracking nutrient intake in Microsoft Excel. Fundamentally, all you need is a list of foods with nutrient composition (carbs, protein, fat, kCal…) and a list of food that you ate. Linking them with a simple VLOOKUP functions and then summing data with a couple of array formulas then gives me summarized nutrition information for specific day, week or month. Just basic Excel formulas, no macros or visual basic programming needed. I only threw in some fancy conditional formatting and graphs that allow me easier analysis and interpretation of data. Additionally, I also implemented tracking various categories of foods (i.e. dairy, dairy products, vegetables, fruits, meat, fishes…), mostly just out of curiosity for how much of specific food groups I eat. I keep this spreadsheet in my Dropbox cloud, so I can access it from everywhere.

As far as nutrient composition of food goes, I get most of the information from Wikipedia, National Nutrient Database for Standard Reference, Wolfram alpha and food labels on food products. If everything above fails, then Google usually comes to the rescue.

Below are some screenshots from the spreadsheet I use.

Master index of food with nutrient composition

Master index of food with nutrient composition

Daily individual food intake, where I note only the date, time, food item and quantity. Nutrient composition is calculated via VLOOKUP function, and conditional formatting automatically separates the days and meals with borders

Daily individual food intake, where I note only the date, time, food item and quantity. Nutrient composition is calculated via VLOOKUP function, and conditional formatting automatically separates the days and meals with borders

Daily summary view, where the data on kCal, carb, protein and fat consumption per day along with some other information is shown

Daily summary view, where the data on kCal, carb, protein and fat consumption per day along with some other information is shown

Weekly summary view, where the data on kCal, carb, protein and fat consumption per week along with some other information is shown

Weekly summary view, where the data on kCal, carb, protein and fat consumption per week along with some other information is shown

Monthly summary view, where the data on kCal, carb, protein and fat consumption per month along with some other information is shown

Monthly summary view, where the data on kCal, carb, protein and fat consumption per month along with some other information is shown

All in all, I would estimate that additional labor for tracking nutrient intake takes me less than 5 minutes per day. I do not find this extra work troublesome as it has become a part of my daily routine. Basically, it’s the same thing as with every other “investment” in our lives: it’s not hard to do something if the benefits outweigh the effort.

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