cd rki
donors
new since yesterday
donated data
(Last updated: )

Great weather quickens the heart

Many things have changed in the last few months; the number of active Covid-19 cases and local Corona-regulation, but also everyday things like the weather. Many of these things can influence the vital data of our donors; for example, lifted lockdowns, bank holidays and good weather may lead to more sport activity and could potentially lead to a high resting heart rate.

One of the big challanges of this project is the identification and correct handling of those numerous other factors.

A good example of a factor that might influence vital data is weather.

What do we expect?

The weather influences the vital data on multiple levels. On one hand can good weather change our behaviour. If donors are more active on days with good weather, this should influence their step counts in particular. So far it’s just common sense.

On the other hand it is known from previous studies, that temperature has a direct influence on our heart rate. At pleasant room temperature our heart rate is the lowest. If we’re cold or sweating, our heart rate increases slightly.

Of course the outdoor temperature is not necessarily the temperature that our body directly experiences.

Rain and Clouds Lead to Less Activity

Weather, of course, has many aspects: temperature, precipitation, wind speeds, cloudiness, and many more. Their influence on the vital data is diverse. Clouds and sunshine influence our behavior but have no direct influence on our body:

Resting heart rate and step counts as a function of cloudiness and precipitation: The resting heart rate of the donors does not correlate with cloudiness and precipitation. But the step count does: the donors walk less if the sky is cloudy or when it’s raining. All data points are daily aggregates.

Here are the mean resting heart rates and step counts plotted against the cloudiness and precipitation (locally weighted depending on donor density). Since weather is just one factor of many, the plots appear quite noisy (e.g. the values are higher on weekends). The lines (linear regression) are supposed to provide guidance and show the general trend in the data. We see that the resting heart rate is completely unaffected from the cloudiness and precipitation (horizontal regression line) but that step count decreases slightly with more rain and clouds (falling regression line).

Temperature Influences Resting Heart Rate

Temperature has a much clearer influence on the heart rate:

Resting heart rate and outdoor temperature Left: The daily aggregated resting heart rate depending on the outdoor temperature. The regression line rises, so on average the resting heart rate increases with increasing temperature. Right: The same values sorted by date. The temperature is encoded by color. We can see the correlation persists during the entire observation period.

The resting heart rate correlates clearly with outdoor temperature. We do not see a heart rate increase for low temperatures. One reason could be that we show the daily average of the temperature, the daily maxima are respectively higher. Also heating and wRM clothes might compensate most of the effect of low temperatures.