By Paul Homewood
The new Lancet report on climate change is now out:
The number of older people dying from heat-related causes has doubled in under 20 years, a report revealed yesterday.
Britain suffered an estimated 8,500 heat deaths among the over-65s in 2018 – more than twice the average for the years 2000 to 2004.
Researchers blamed heatwaves and said healthcare is ‘at risk of being overwhelmed in the future’ unless drastic action is taken to halt climate change.
The Lancet Countdown report said rising temperatures will increasingly threaten health, but cutting red meat consumption and air pollution can help.
It stressed that heatwaves are one of the major health impacts of climate change and over-65s are the most vulnerable. The research also revealed the UK was hit by 5.6million hours of lost work in 2019 due to heatwaves.
The climate crisis made 2019 a year of record temperatures, with a highest ever in the UK – 38.7C (101.66F) – in Cambridge.
Figures show heat-related deaths of vulnerable people across the world have increased by 54 per cent in the past two decades, claiming 296,000 lives in 2018.
However, this year they have added a new section on heat mortality:
Although the report does not specifically give numbers for the UK, it is claimed that Britain suffered 8500 heat deaths amongst the over 65s in 2018, double the rate between 2000-2004. This claim clearly comes from the Lancet, as it has been plastered all over the media this week.
The report goes on:
Paul Homewood comments:
I am sure the German government will be delighted to learn that its neglect of the elderly population has led to 20,200 heat deaths!
But, of course, nobody has died with “heat related” written on their death certificates. As usual, with climate science, it is all based on computer models, which operate on a Garbage In, Garbage Out basis, otherwise known as GIGO.
This model is programmed with the assumption that the hotter it is, the more likely old people are to die.
For some reason, the Lancet conveniently forget to mention that cold kills far more people than warmth does. Worldwide, scientists have worked out that cold weather is 20 times as deadly as hot weather, even in hot countries such as India. Since this study was actually published by the Lancet in 2015, you might have thought they included it in their new findings!
In Britain, of course, there are tens of thousands of excess deaths in winter. In contrast, summer months always record the lowest number of deaths in the year.:
As far as the UK is concerned, at least, there is no need for the Lancet to employ their shonky models. We have the actual mortality data, as supplied by the ONS.
We cannot directly compare the summer of 2018, with that of 2004, because the total number of deaths occurring during the year as a whole has been steadily rising since around 2009. Currently annual death tolls are about 30,000 higher than in 2004:
This is not because we all less healthy, but because the population is both getting larger and older. For example, there are now many more over 80s than there was two decades ago due to the fact that we are all living longer on average; and as that is when most people die, the number of deaths has also started to rise again.
Put simply, death is playing catch up!
That is why the ONS look at Age-Standardised Mortality rates when comparing trends.
And when we look age-standardised mortality in July and August for over 75s, we find that even in 2018 it was much lower than in 2004. (The series only began in July 2020, so there are no figures for June):
And from the weekly registrations of deaths, we can also chart the summer deaths for over 65s:
The heatwave summer of 2018 actually recorded the second lowest number of deaths in the five-year period.
Clearly that heatwave had no measurable effect on death tolls amongst the elderly at all.
All of this should have been very evident to the Lancet’s “experts”, and very easily accessible. We also know from COVID research this year that all other EU countries have similarly rigorous data available for mortality rates.
So why did they choose to ignore all of this real world data, and instead use phony results from dodgy computer models?