In a previous post, I mentioned that I get a runny nose when I go for a walk in the mornings or a run in the evening. It’s not terrible, but is annoying and prevents me from breathing comfortably through my nose. I hypothesized that this was caused by allergies and, with great feedback from readers (Reddit, QS forum), designed a set of experiments to check whether this was the case.
In this post, I will report the results from the first experiments, a blinded, placebo-controlled test of exercising after taking a fast-acting antihistamine.
TL;DR:
Fast-acting antihistamine reduced my rhinitis, but that could be due to preventing a mild allergy or just drying out my nasal passages.
All other allergy medication I can find also reduces mucus production and the other intervention I was planning (wearing an N95 mask) blocks allergens, but will also increase the temperature of the air I breathe and thus not distinguish between allergy and cold as the cause.
Does anyone know of a test a way to block/prevent allergies that doesn’t dry out nasal passages or increase the temperature of the air you breath?
Historically, there hasn’t been a lot of low-carb replacements for flour available, mostly almond flour, coconut flour, and resistant starches. Similar to other low-carb products, a ton of new flour replacements have hit the market in the last few years. As always, the net carb counts look good, but I wanted to test them to see if they really hold up (see evidence of blood glucose impact of dietary fibers here & here).
Between my own searching and reader recommendations (1, 2, 3), Foods. I tested 18 flours from 6 different categories (grouped by main ingredient). Here’s my overall conclusions:
Most Similar to Wheat Flour: Carbalose
<30% BG impact of wheat flour, <20% of white bread
texture & water uptake very similar to wheat flour
Lowest BG impact: Ground chia seeds
12% of wheat flour, 8% of white bread
Best Binders: Gluten, chia seeds, flaxseed, and psyllium husk
These work great to tune the texture of other flour replacements
Which one is best to use probably depends on the specific recipe/desired texture
Best Pre-made Blends: King Arthur Keto Flour & Carbquik
King Arthur is a flour substitute, though more elastic/chewy
Carbquik is like Bisquik and great for biscuits, pancakes, muffins, and other airy baked goods.
In a previous post, I mentioned that I get a runny nose when I go for a walk in the mornings or a run in the evening. It’s not terrible, but is annoying and prevents me from breathing comfortably through my nose. I hypothesized that this was caused by allergies and proposed some experiments to check whether this was the case.
I got great feedback on that post, both from Reddit and the Quantified Self forum. In particular, several commenters suggested:
Making sure the experiments could distinguish between cold & allergens as the cause
Testing indoor exercise & no exercise in the same outdoor locations
Using an N95 mask as an alternative to allergy medicine as means of assessing whether allergens are the cause
Keeping track of weather and pollen counts during the experiment as potential confounders
Following up on these suggestions, I did a few quick experiments to narrow down what might be going on:
I sat outside, not exercising, in the same location I take my morning walk. After 1h, I did not get a runny nose. I then started walking and developed a runny nose within 15 min. (the same intensity as has occurred every day since I’ve started monitoring).
I used a rowing machine to exercise indoors at maximum intensity for 30 min., the same as my evening run. I did not develop a runny nose.
Based on these two observations and the fact that I’ve consistently gotten a runny nose on my morning walks for at least 3 weeks, it seems like the cause has to be either allergies or cold and exacerbated by physical activity.
To test the two hypotheses, I will run the following experiments:
Test 1: Walk while wearing an N95 mask both with and without the particulate filter.
The experiment will be randomized and blinded by having another person load/remove the filter
I will run 2 tests for each condition, recording whether or not I get a runny nose and it’s severity.
If I get the runny nose without the filter, but not with it, that strongly suggests the cause is allergies. If both conditions prevent a runny nose, that suggests the cause is temperature.
Test 2: Exercise (walk & run) after taking allergy medication
Take fast-acting allergy medication or a placebo 1 hour before exercising.
The experiment will be randomized and blinded by placing the pills inside of opaque gel caps and have another person randomize the treatment days for me.
If no effect is observed, take long-acting allergy medication or a placebo on alternating weeks.
I will run 3 tests for each condition, recording whether or not I get a runny nose and it’s severity.
During all experiments, I will record temperature, pollen count, and other notable weather conditions. If it is raining or unusually windy (very uncommon where I live), I will postpone the experiment to the next day.
These experiments will start next weekend, so I expect to have results to share in 3-4 weeks.
Previously, I proposed some analyses and breathing experiments to try to identify potential causes for and ways to reduce my high blood pressure. I got great feedback on that post (thanks everyone!) and have also done some preliminary breathing experiments. Based on that, I’ve finalized my experimental and analytical approach and am ready to start. This post will serve as the pre-registration of the experiments.
Details
Purpose
To identify environmental or controllable factors that have a significant impact on my blood pressure.
To quantify the effect of known interventions for reducing blood pressure.
To find a set of interventions that enable me to reduce my blood pressure below 120/80 mmHg.
Background
Figure 1. Weekly average of blood pressure as measured by Omron home blood pressure monitors.
Figure 2. Cumulative incidence of cardiovascular disease vs. time for different blood pressure groups from a study of the South Korean nationwide health screening database (6.4M participants).
Table 1. Rate of cardiovascular disease for different blood pressure groups from a study of the South Korean nationwide health screening database (6.4M participants).
Given this, I’d like to see if I can reduce my blood pressure and reduce the strain on my heart and circulatory system.
There are numerous medications that lower blood pressure, but all risk of side effects. Before I pursue that route, I’d like to better understand the cause of my elevated blood pressure and see if any diet or lifestyle interventions can ameliorate it.
As mentioned above, I’ve been measuring my blood pressure for the past 4 months, along with blood glucose, sleep, weight, and exercise. This provides a (hopefully) rich dataset for identifying environmental or lifestyle factors that influence my blood pressure. Notably, I’ve noticed that my blood pressure is elevated on days after I’ve had low blood sugar the night before, indicating a possible effect (no statistical analysis done).
As a quick test of this approach, I did one-off tests of 7 different breathing protocols. I tested one each morning after arriving at work, measuring my blood pressure before and after the protocol. I used the app iBreathe to help regulate my breathing. The results are shown below.
Change in blood pressure following different breathing protocols. Protocols descriptors are Inhale Time (s)/Hold Time (s)/Exhale Time (s)/Hold Time (s), Total Duration (min.).
With the exception of one protocol (8s inhale/8s exhale for 5 min.), I did not see a significant drop in blood pressure. However, I saw a large rise in blood pressure (+7/+3 mmHg) when I did not use a breathing protocol. Given this, I think a more extensive experimental test, focused on the longer inhale/exhale time is worth trying.
Proposed Experiments
Phase 1: Identify Potential Causes of Elevated Blood Pressure from Existing Self-Tracking Data
Data
Blood pressure:
systolic and diastolic blood pressure
Measured by Omron Evolve
Glucose:
Same day: fasting BG
Previous day: average BG, time low (70, 60, & 50), time high (120, 140, 160), & coefficient of variation
Previous evening (after 7p): same as previous day
Measured by Dexcom G6
Sleep:
Time asleep, number of wake-ups, early rising (time woke before alarm)
Measured manually and by Apple Watch (less reliable but more data)
Other heart markers:
pulse (sleeping, morning, and awake), heart rate variability
Type of exercise the previous day (aerobic vs. strength training) and frequency of aerobic exercise
Manually recorded
Analysis
A mixed effect model will be used to calculate the effect size, standard error, 95% CI, and p-value for the correlation between each metric and systolic and diastolic blood pressure
Effects will be of significant magnitude if a reduction of 5 mmHg can be achieved via a practical variation in the correlating metric.
Given the large number of metrics being looked at, I will use p-value thresholds of:
0.02 for planning testing interventions
0.05 for follow up experiments to confirm the correlation
0.1 for further monitoring/assessment as I get more data
Phase 2: Testing Deep Breathing to Lower Blood Pressure
Background
Numerous studies, reviews, and meta-analyses have shown deep breathing to lower blood pressure in both the short and long-term (example 1, example 2).
Effect sizes are moderate (3-5 mmHg) and statistically significant for large patient populations (>10,000 patients in some studies).
Numerous breathing protocols have been tested, with varying results.
My own quick tests (see above) suggest a possible effect.
Approach
Measure blood pressure and pulse before & after the following protocols:
8s inhale, 8s exhale
Normal breathing (read and do not use app to regulate
Normal activity
Each protocol will be tested for 5 & 15 min.
Each protocol/time combination will be measured five times.
Conduct measurements 1/day in the mornings.
If any protocols show significant reduction in blood pressure (>3 mmHg), optimize the protocol and design/execute an experiment to test the long term effect.
Measurement
Blood pressure and pulse will be measured with an Omron Evolve.
Analysis
Student’s t-test will be used to test if the blood pressure change for any of the protocols is different from that of normal breathing.
These experiments will start this week, so I expect to have results to share in ~4 weeks.
I’ve started paying more attention to my breathing in the past few weeks and have noticed that when I go for a walk in the mornings or a run in the evening, I develop a runny nose that goes away shortly after I go back inside. It’s not terrible, but is annoying and prevents me from breathing comfortably through my nose.
From a quick search, my symptoms match closely with exercise induced rhinitis (list of articles). Numerous studies have found that exercise induced rhinitis is usually caused by allergies. I have never had nasal allergies, but it’s possible I’ve developed them or that they’ve always been mild enough that I haven’t noticed.
I’d like to determine whether my symptoms are, in fact, being caused by allergies and, if so, if there’s any simple interventions I can do to mitigate them.
Here’s my plan:
Step 1: Test if the symptoms are caused by just being outside or only during exercise
Go outside to the same location where I exercise and wait for 30 min. (same length as walks/runs).
Record whether I develop a runny nose and its severity.
Step 2 Test if the symptoms are ameliorated by allergy medication
Take fast-acting allergy medication or a placebo 1 hour before exercising.
Record whether I develop a running nose and its severity.
This experiment will be blinded by placing the pills inside of opaque gel caps and have another person randomize the treatment days for me.
Run the experiment for 10 weekdays & 4 weekend days (exercise locations differ)
If no effect is seen, repeat this experiment with long-acting (24h) allergy medication, but randomize by week instead of by day.
Questions
Does this approach seem reasonable? Any other measurements/tests I should try?
Does anyone else have this problem? If so, any recommendations for interventions to try?
