An audience…

I must admit I write this blog mostly for my own benefit. If I write about a goal or an achievement, or even a feeling I have about something, the blogging platform conveniently adds a timestamp, so if I look at a post a year later, say, I avoid any tricks my memory might want to play. I’ve noticed, for example, that I mentioned a goal in here – when I achieved that goal I thought I might have been attempting it for six weeks or so, but when I looked on here I found that I’d actually been writing about attempting the goal for some six months.

I happened to look at Google/Blogger ‘s stats page today and was quite surprised. I kind of realise that most of the stats are down to me, where I proof-read recently-published posts to check grammar  and just to check that the post makes sense. But whenever someone visits the blog, Google captures things like the user’s operating system and browser type. I know that each browser presents itself slightly differently when it requests a web page, and by storing and analysing the differences, you can deduce what that browser is. This approach also tells the platform (Windows or Macintosh, for example). And by capturing the user’s IP address, the platform can do a partial reverse lookup and tell (at a high level) a user’s location. For example, if someone looked at my own computer’s IP address, they could find out that I come from the UK, and my ISP. But they couldn’t know my name or address, say. Of course, the ISP is able to link my name and physical address to my computer’s IP address, or at least they know whose account they leased that IP address to, which is how law enforcement agencies can track down people who, say, threaten other people online. If the law enforcement agency can be bothered to get a court order to make the ISP tell them who is involved, that is.

Anyway, I look at the stats, and although most of the hits are down to me, I can see signs that tell me that not every hit is down to me. I’m seeing non-UK hits, from the US, Ireland and Australia. And I use the Firefox browser on pretty much all my devices, yet I see hits from things like Internet Explorer and Safari etc.

So, if you’re one of the people who has fallen into my blog……a big hello to you!

Daily Diary

I’d dearly love to build up a picture of what happens to my sugar throughout the day. Ideally, it should be pretty much a flat line, so I wonder how much I vary from that? Today is a bank holiday here in the UK so I’m going to be stuck at home all day. To this end, I’m going to not only record what I eat (I’ve done this occasionally anyway) also to take my meds as normal, but also to record my sugar every hour or so. As regards eating, I’m going to try and keep the day as “typical” as possible, obviously subject to hunger pangs.

I’ll start by recording my “getting up” sugar, and at the end of the period will try to construct a graph to make things easier to interpret. Unfortunately the blogging platform that I use ( doesn’t allow me to present something as sophisticated as a spreadsheet in my entries, so I’ll unless I can think of a better option, I’ll probably end up taking a screenshot and posting the image or two….The values themselves I can put in a table.

Blood Sugar Details – 30-Mar-18

Time of Day Sugar (mmol/l) Event
08:30 10.2 Getting up test
09:30 10.4 Test
09:45 Morning Meds plus breakfast. Insulin (44 Units), BP Meds, then Redbush Tea (no milk), Porridge (milk and oats, garnished with sultanas). The food should raise my sugar, but the insulin will lower it
10:30 12.2 Test
11:30 13.1 Test
12:30 10.7 Test
13:30 7.7 Test
13:45 Lunch. 3 pieces wholemeal bread, sliced chicken breast sandwiches, low fat/sugar yoghurt, clementine, black tea
14:30 9.4 Test
15:30 10.6 Test
16:30 Afternoon nap!
17:00 13.8 Test
17:15 Snack: Tea and 4xCrackers
18:10 13.0 Test
19:00 12.1 Test
19:45 Evening Insulin (44 units)
20:00 13.4 Test
20:15 Supper: dusted fish, oven chips, peas, tea, zero-fat yoghurt
21:00 12.3 Test
21:45 14.2 Bedtime Test
05:30 Saturday 11.3 Test. Got up for a pee

These numbers all translate into a graph below. I’ve tried to adjust the colours so as to improve the contrast:

Blood Sugar 30-Mar-2018


  • it looks a bit like a sine wave, centred around 10 mmol/l and varying maybe ±5 mmol/l, give or take. I’m not sure how I can reduce the variation unless I lower my second insulin dose, and then add another one at 3 or 4PM
  • First thing in the morning, before I eat anything, my sugar stats pretty steady. I wonder, if I just spent the day not eating and not taking meds, whether that would still be the case? Logic would dictate that just day-to-day living would consume energy, so eventually sugar levels would get lower
  • The morning insulin took me down to about 7, so I’d be reluctant to increase it further just yet
  • I seemed to reach a peak up to about six o’clock, then my sugar went down naturally, without insulin. I didn’t have my second insulin dose until around 8PM
  • That my basal level was slightly higher on Saturday morning than on Friday morning is probably something to do with having chips for supper. For that reason I’d be reluctant just to perform a blanket raise my evening insulin, irrespective of the food I eat
  • The fast insulin has nowhere near the effect of the slow insulin. But there again, it does form only a quarter of the mixture
  • I don’t eat much food these days!
  • I need to be careful about how much I read into these numbers, as in many cases we could be talking about the tolerance of the glucometer itself. I wouldn’t want to assume that the glocometer was any more accurate than +/- 10%, despite what marketing material might say
  • The glucometer needs new batteries and my fingers (bear in mind I test on just one hand) feel like a pin cushion!