On Virusvaria we saw last week that in 2025 the greatest excess mortality will again occur among women between 30 and 50 years old. In 2024, excess mortality within this group was highest in the 40-50 subgroup, in 2025 this was in the younger 30-40 subgroup. In the comments the question was asked whether the increase in the number of migrants influences the excess mortality of the entire group. We will look at that in the article below.
Method
We use exponential regression per 100,000 of the group based on the period 2010-2019. A characteristic of this method is that the expected mortality changes annually by a certain fixed percentage over time. The advantage of this method is that mortality will always remain greater than 0 in the future. CBS indicates the numbers of deaths per age for total mortality. If you want to break down these numbers by migration background, the narrowest age group that CBS distinguishes is five years. However, practice shows that when five-year groups are used, the baseline hardly differs from the one you get when one-year groups are used. CBS has not yet published the numbers of deaths by background for 2025, so we are looking up to 2024.
We first determined the separate baselines and therefore the excess mortality for people with a migration background and people with a Dutch background. Finally, we summed these up to get the totals, and luckily, these pretty much match the totals from the earlier article on Virusvaria. Within the 30-50 group, we distinguish between the subgroups 30-40 and 40-50.
Finally, one more important point to keep in mind. Determining excess mortality is not an exact science. Coincidence can play an important role, not only in determining the baseline but also in the calculation of excess mortality. So there is always some uncertainty. The influence of chance increases as the expected numbers of deaths in a group become smaller. We will also see that in the graphs. First the graphs with the absolute figures. Because these must be interpreted against a faster growing group with a migration background (with a resulting rising baseline), the graphs with the relative mortality per group are also shown at the bottom of the article.
Results
Women 30-40 years
Six graphs are shown, three for each age group. We start with the group of 30 to 40 year old women with a migration background:
Women 30-40, Migration background
This is a good example of where chance plays a significant role. Major fluctuations occur from year to year in the period 2010-2019. The baseline increases over time, which implies that the group size increases. When using this baseline, there is certainly excess mortality from the start of the corona period, but this remains within limits.
Women 30-40, Dutch background
Mortality up to 2019 shows a decline up to and including 2014, followed by a short increase up to and including 2016 and then a decline again. There is less spread up to and including 2019 than in the first graph. Based on this baseline, excess mortality in this group is greater, both absolutely and in percentage terms.
Combined, this leads to the following graph:
Women 30-40, Total
The shape of the second graph is clearly reflected in the total graph. Within this subgroup, people with a Dutch background make the most significant contribution to excess mortality.
Women 40-50 years
Would this be different for the 40-50 age group? We first look at people with a migration background:
Women 40-50, Migration background
Here too, chance plays a significant role due to the group size. We see higher mortality in 2011 (and to a lesser extent in 2010) than in the other years up to and including 2019. This does ensure that the baseline is steeper than if these peaks had not occurred. Then the expected mortality would be approximately 280 over time, with perhaps a small increase from 2022. But even if you use that as a baseline, excess mortality will remain significant from 2020.
Women 40-50, Dutch background
Here 2012 stands out with a clearly higher than expected value. In contrast, the values after 2012 to 2019 are close to the baseline. The excess mortality does not seem that great, but that is also because the difference between the maximum and minimum value of mortality is very large. This is also reflected in the baseline: expected mortality will halve between 2010 and 2022.
If we take the two subgroups together we get the graph below:
The slope of the baseline is slightly less steep; from 2010 to 2024 we see almost a halving of expected mortality, which was already around 2022 in the previous graph.
Including the excess mortality among people with a migration background results in a higher excess mortality in both absolute and percentage terms.
In summary, the excess mortality percentages are as follows:
In contrast to the 30-40 group, excess mortality among women with a migration background is clearly greater in the 40-50 group. However, excess mortality is also significant among women without a migration background, and the latter applies to both subgroups.
Is the excess mortality among young women due to migration? No, but migration makes the largest contribution for the 40-50 percentage group. Further research will have to reveal what the causes are.
Relative figures
Women 30-40 years
Migration background
Dutch background
Total
Women 40-50 years
Migration background
Dutch background
Total
Thanks for this additional analysis.
What I see is that - for these age groups - migration background cannot explain the phenomenon of excess mortality since 2020. I come to this conclusion because the graphs of the groups born in the Netherlands still show the 'kink' in increase in mortality from 2020.
What I also find interesting, but which is separate from the question of whether there will be excess mortality from 2020, is the phenomenon that from at least 2010 (earlier figures are not included in the graphs) to 2029, there has been a spectacular decline in annual mortality. How come?
If I remember correctly (I have searched for this before), this probably has to do with a 50% lower morbidity from cardiovascular diseases (compared to before the year 2000). Cardiologists then say: 'There you go, statin!' But I think that simple smoking cessation advice explains this spectacular decrease (in CVD morbidity and total mortality).
I wonder what would happen to mortality if other simple advice (such as quitting smoking) were implemented at population level, such as the advice: don't get vaccinated, eat meat (IS part of the 5 bracket, no matter how sad I think it is for the animals), or try to eat as much non-processed food as possible? Ideas that I don't think you need to have a bright mind for, and which is a reason that these ideas will not come from the bright minds in our medical world.
Finally..
Well, my field of expertise (was)… In the Netherlands and now also in Germany there was a study: 'Eating meat prevents Alzheimer's' and in the trade magazine the following article was published under the article: 'In the Netherlands, large institutions are increasingly obliged to eat plant-based food'… My advice: consciously eat meat, as animal-friendly as possible and with a variety of white, red, organ, game and fish meat. For the migrant group, the problem is not the meat (but for the animal...) but the extreme excess of sugar and deep frying. Vitamin D deficiency also plays a major role. Money plays the biggest role and I don't mean the groceries but the industry. The WUR has become a WEF hub and where previously bright minds were (somewhat) allowed to express their own findings, in 2020 this is just as prohibited as in the medical world. For decades, the policy in healthcare has been “intervention with medication and/or operations and a tiny pot for prevention”. There is now a little more room for prevention (tending towards patronizing), but with conflicting advice due to the climate... Nutrition is not an explanation for a sudden increase in mortality from 2021.