Lives Saved
- References
- Deaths: Data Notes
- Population: Centers for Disease Control and Prevention, National Center for Health Statistics
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- There were a total of 173,938 deaths in New York in 2022
- 99,610 of all deaths were among females
- 46,709 of all deaths were among those aged 30-34
- 594 of all deaths were among women aged 30-34
- 31,047 of all deaths were from Unknown Causes
- 14,836 of female deaths were from Unknown Causes
- 374 deaths from Unknown Causes were among those aged 30-34
374 deaths from Unknown Causes were among women aged 30-34
2022 vs New Normal™ for women aged 30-34 in New York
- 374 of 594 total deaths were from Unknown Causes
- 62.96% of all deaths were from Unknown Causes
- This is up 8% compared to Old Normal rates.
- 339 of 399 total deaths would have been expected under Old Normal conditions.
- 35 excess deaths from Unknown Causes in 2022.
- 195 excess All Cause deaths in 2022.
- 12 fewer than expected deaths from Unknown Causes (2015-2022)
- 825 excess All Cause deaths over the first 8 years of New York’s New Normal™.
- To show this year’s deaths from Unknown Causes are up 8% compared to Old Normal rates, we need to calculate the rates for both 2022 and for the Old Normal.
Remember, death rates are calculated to answer these questions:
- “How many women aged 30-34 were there?” and
- “How many of them died from Unknown Causes?”
The following 2 charts provide this information:
Deaths – Unknown Causes – Female – Aged 30-34 | New York, United-states
Population – Female – Aged 30-34 – [2000-2022] | New York, United-states
From the charts, we can see that in 2022, 374 of 700,481 women aged 30-34 living in New York died from Unknown Causes.
374 ÷ 700,481 = 0.00053 (2022 CDR)
The table shows there were a total of 4,892 deaths from Unknown Causes among 10,114,080 women aged 30-34 living in New York in the 15 years immediately prior to the New Normal™.
4,892 ÷ 10,114,080 = 0.00048 (Old Normal CDR)
We can use the Old Normal rate to predict this year’s deaths:
2022 pop X Old Normal CDR = expected deaths
700,481 X 0.00048 = 339 expected deaths
The difference between actual and expected deaths shows lives saved or lost:
374 – 339 = 35
Dividing the actual deaths by the expected deaths gives us the comparative rates:
374 ÷ 339 = 1.0815
This reveals 35 lives lost and is 108.15% of what we expected (an increase of 8%) in deaths from Unknown Causes among women aged 30-34 living in New York in 2022, as compared to the Old Normal.
This is the same method used by Public Health to calculate the 5-yr CDR (Cumulative Death Rate):
2,326 ÷ 4,906,735 = 0.00047 (5-yr CDR)
700,481(2022 pop) X 0.00047 = 332 expected deaths
The difference between actual and expected deaths:
374 – 332 = 42 or 42 lives lost
Divide actual deaths by expected deaths:
374 ÷ 332 = 1.1030 or an increase of 10%
for deaths from Unknown Causes among women aged 30-34 living in New York in 2022, as compared to the previous 5 years.
Compare our Old Normal to the 5yr CDR. Does it tell the same story your TV does?
Finally, the same method can also be used to compare our Old Normal rate to the New Normal™ rate:
New Normal™ population X Old Normal rate = expected deaths
5,607,216 X 0.00048 = 2,712 expected deaths
The difference between actual and expected deaths:
2700 – 2,712 = -12 or 12 lives saved
Dividing the actual deaths by the expected deaths:
2,700 ÷ 2,712 = 0.9754 or a decrease of 2%
in deaths from Unknown Causes among women aged 30-34 living in New York in the New Normal™, as compared to the Old Normal.
The world has been led to believe that a deadly pandemic swept the globe beginning in 2020, causing an increase in death rates, especially among the elderly
The data show that death rates began to increase in 2015, immediately upon implementation of the UN’s 2030 Agenda for Sustainable Development, that young adults have experienced ever-increasing death rates since, and that death rates among the elderly have remained relatively stable.
Return to the top of the page to select another age category.
Deaths/100,000 female 30-34 from Unknown Causes
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