CDC: Life Expectancy Increased in Most States in 2022
Their latest report. However, as their 2019 visualization shows, life expectancy still hadn’t caught up to pre-pandemic levels:
https://www.cdc.gov/nchs/data-visualization/state-life-expectancy/index_2019.htm
Yes there is.
A really good overview of life expectancy trends around the world, and how to understand what is going on. I wonder what the impact of AI will be on these trends…:
The “Death of Despair” Hypothesis is Dead; Enter “Deaths of Dislocation.”
Current life expectancy data reveals a K-shaped divergence masked by mean statistics. While the top 5% of US earners now outlive peers in Norway and the UK, the bottom 5% have suffered a catastrophic loss of approximately 15 years of life expectancy. This decline is not driven by metabolic disease (CVD, cancer) but by “external causes”: substance abuse and suicide. Crucially, the prevailing “Deaths of Despair” narrative (Case & Deaton) is statistically inferior to a “Deaths of Dislocation” model.
Recent longitudinal data (Glei et al., 2024) demonstrates that subjective feelings of despair (depression, distress) are weak predictors of mortality compared to objective structural factors: labor force detachment and social isolation. The mechanism of mortality is not purely psychological anguish but the kinetic availability of lethal means (e.g., fentanyl, pesticides) combined with the loss of “communal utility” (employment). Interventions focusing on individual therapy or financial compensation (UBI) without restoring social function are projected to fail. Effective protocols must be structural (means restriction) and communal (group-based labor), not clinical or pharmaceutical.
| Claim from Video | Speaker’s Evidence | Scientific Reality (Current Data) | Evidence Grade | Verdict |
|---|---|---|---|---|
| Unemployment/Isolation is a stronger predictor of death than “Despair” | Longitudinal analysis of “thousands of Americans” (2023/24). | Confirmed. Glei et al. (2024) found labor force detachment and low social integration were strongly associated with drug/suicide mortality, while distress measures were not. | Level B (Longitudinal Cohort) | Strong Support Source |
| Suicide rates are driven by “ease of means” (e.g., Pesticides) | Sri Lanka agricultural revolution and subsequent bans. | Confirmed. Pesticide bans in Sri Lanka reduced suicide rates by ~70% (1995-2005) without changes in mental health prevalence. | Level C (Ecological / Natural Experiment) | Strong Support Source |
| “Men’s Sheds” improve health outcomes for isolated men | Anecdotal success in Australia/Ireland; comparison to individual exercise. | Mixed/Plausible. Systematic reviews show high qualitative value (social connection) but “small” or “unclear” quantitative effects on physical biomarkers. | Level C (Observational/Qualitative) | Experimental / Plausible Source |
| Substance abuse/suicide kills more under-55s than CVD/Cancer | Aggregate mortality trends for bottom 5%. | Confirmed. CDC data (2021) shows “Unintentional Injuries” (inc. overdose) is the #1 cause of death for ages 1-44, surpassing cancer/heart disease. | Level A (Epidemiological Data) | Strong Support Source |
Protocol 1: Means Restriction (Suicide Prevention).
Action: Physical removal of high-lethality agents (firearms, toxic chemical concentrates) from the immediate environment of at-risk individuals.
Rationale: Suicide is often impulsive; increasing the “kinetic friction” of the act significantly lowers completion rates (Sri Lanka data).
Protocol 2: Social Integration via Employment.
Action: Prioritize retention of employment or immediate placement in “communal labor” over passive financial assistance (disability/welfare) for capable individuals.
Rationale: Labor force detachment is a verified mortality multiplier independent of income (Glei et al., 2024).
Protocol 3: “Men’s Sheds” / Task-Oriented Socialization.
Action: Engage isolated males in side-by-side cooperative tasks (woodwork, repair, team sports) rather than face-to-face therapy.
Rationale: Observational data suggests high adherence and reduced isolation for men in task-based groups, mitigating the “Anglophone isolation” risk.
Protocol 4: Social Gaming as Digital Intervention.
Action: If digital interaction is necessary, utilize platforms requiring synchronous voice/team cooperation (e.g., MMOs, squad-based games) rather than passive social media or text-chat.
Pathology: The “Cohort Scarring” & Dislocation Model
The transcript rejects a purely biochemical model of depression in favor of a Sociogenic/Structural model of mortality.
Related: maternal mortality ratio is getting worse each year in the US. Now so bad that it’s worse than China.
Some states are doing better, but even the best states (California and Washington) are performing like Kazakhstan and Turkey:
Similar picture for child mortality:
Thanks. But mortality increased by +21% between 1985 and 2003, then +34% between 2003 and 2017 then -7% between 2017 and 2023. And ChatGPT says that the UK, France, Italy, and Nordics (among others) are like the US in terms of reporting. So that doesn’t explain the US under performance. Although it might explain the Chinese overperformance (but probably not the overall improving trend).
And to refine a bit further, it was flat from 1985 to 1998, then all that increase you noted came in the last five years.
Plotting the actual data you mentioned:
The US was literally murdering mothers during covid.
And look what Thatcher and Major did to the 80s-90s UK numbers! Thank god Blair got a grip on things.
Why do some people age faster than others? USC President Kim and global aging expert Eileen Crimmins – the Professor of Gerontology at USCLeonardDavis. Explore the science behind healthspan, longevity, and the limits of biohacking.
This transcript details a high-level population health and gerontological analysis by Dr. Eileen Crimmins, focusing on the epidemiological realities of human aging, demographic disparities, and the biological validation of social determinants of health. The core thesis rejects the fragmented approach to age-related disease (e.g., treating cardiovascular disease and cancer as distinct entities) in favor of targeting a universal set of molecular and cellular changes—the hallmarks of aging—that underlie all late-life morbidity.
Crimmins presents a stark critique of the current state of consumer longevity interventions (“biohacking”). She identifies a massive translational gap between population-level epigenetic research and individualized, direct-to-consumer anti-aging protocols. Notably, she warns that single-individual longitudinal tracking using current epigenetic clocks yields unacceptable noise levels—fluctuating by 8 to 10 years within a single subject over mere months—rendering short-term clinical decision-making based on these commercial tests scientifically invalid.
A significant portion of the analysis focuses on the macroscopic failure of the United States healthcare system to optimize healthspan. While the US excels at catastrophic care and extending the lives of older adults with established pathologies, it fails fundamentally at primary prevention. Consequently, the US has engineered an “expansion of morbidity,” where lifespan is artificially propped up by medical technology, but healthspan remains stagnant or degrades. US life expectancy peaked in 2014 and currently ranks in the 60s globally, trailing behind nations like South Korea, Singapore, and Japan. Crimmins argues that the most potent levers for biological aging are not found in isolated molecular interventions deployed in late adulthood, but rather in the mitigation of early-life social stressors, childhood infectious burdens, and persistent behavioral liabilities (obesity, physical inactivity, and substance abuse) that hardwire accelerated epigenetic aging long before clinical symptoms manifest.
| Claim from Video | Speaker’s Evidence | Scientific Reality (Current Data) | Evidence Grade | Verdict |
|---|---|---|---|---|
| Epigenetic age can fluctuate 8-10 years when measured daily in one person. | Recent un-cited meeting presentation. | First-generation epigenetic clocks (e.g., Horvath 2013) suffer from significant technical noise. Next-generation principal component (PC) clocks and rate-of-aging clocks (DunedinPACE) have reduced this variance, but technical and biological noise in consumer tests remains a major barrier to individual tracking. | Level B | Plausible |
| Traditional clinical biological age correlates ~0.65-0.70 with epigenetic age. | Personal/Institutional cohort data. | Validated. Studies comparing composite clinical biomarkers (like PhenoAge) with DNA methylation clocks show moderate to strong correlations, confirming they track overlapping but distinct biological pathways. (Levine et al., 2018) | Level C | Strong Support |
| US life expectancy ranks in the 60s globally and peaked in 2014. | Demographic data. | Accurate. According to the UN Population Division and WHO, US life expectancy peaked around 2014 (78.9 years) and subsequently dropped due to cardiometabolic disease, COVID-19, and the opioid epidemic, currently ranking behind ~60 other nations. (CDC NCHS Data) | Level A | Strong Support |
| Early life infections dictate late-life mortality (Cohort Morbidity Phenotype). | Research with Caleb Finch. | Strongly supported by historical demographic data. Reduced inflammatory burden from childhood infections correlates with reduced cardiovascular and neurodegenerative disease decades later. (Finch & Crimmins, 2004) | Level C | Strong Support |
| Silicon Valley “biohacking” substances lack proof for delaying human aging. | Expert opinion/observational critique. | Accurate. While pre-clinical models show lifespan extension via rapamycin, senolytics, and NAD+ precursors, there are zero completed human RCTs proving lifespan extension or definitive epigenetic reversal in healthy populations. | Level A (Absence of Data) | Strong Support |
| Social hardships in childhood accelerate epigenetic aging by the late 20s. | Cohort studies (e.g., Health and Retirement Study). | Early-life socioeconomic disadvantage, trauma, and systemic discrimination are robustly associated with accelerated DNA methylation aging and telomere attrition in young adulthood. (Simons et al., 2021) | Level C | Strong Support |
Because this transcript originates from a population health demographer rather than a clinical trialist, the “protocol” shifts from acute pharmacological interventions to systemic and environmental risk mitigation.
High Confidence Tier (Protocols backed by robust longitudinal data)
Experimental Tier (Mechanistically plausible but requiring long-term human validation)
Red Flag Zone (Claims debunked or lacking safety/efficacy data)
I also wonder how much maternal age plays into this. It’s well known that increased maternal age is a risk factor for more complicated pregnancies and higher rates of adverse outcomes.
For context, in the US women had their first child at 21.4 years old in 1970. Today the first birth is when the woman is 27.5, and the average for all births is 29.9. In women with a university degree, it’s 31.
In China, mothers are now an average age of 28.8, and in major cities it’s >32.
It strongly correlates with wealth and maternal education level and seems to be a global inevitability as every country gets wealthier.
Out of interest, the earliest births in the world are Bangladesh, with an average first birth at 18, and an overall average of 25.7.
I think we have to still point out that the actual rate is pretty low overall. Those are deaths per 100,000 live births, so even the worst data point is 31 per 100,000, or 0.03%. Of course every one is tragic, but maternal deaths are still thankfully rather uncommon.
Given how much healthcare costs are increasing in the US, and all salaries aren’t increasing that much, it makes sense that quality is decreasing for those who are price sensitive:
8 posts were merged into an existing topic: Optimal Blood Pressure we Should Target? Systolic Under 110 or 100?
Air pollution is a much larger killer than I thought! I have noticed a big impact of my indoor HEPA air purifiers.
It’s also good to ‘burp’ your house by opening up windows and doors to let fresh air in.
Causes and extent of avoidable mortality across the european union: insights for advancing healthy aging
Yes, this is becoming quite a bit one. I was at a cardiac conference last year where the presenter made a convincing case that air pollution was also a driver of cardiovascular disease. Plus lots of spillover - lung diseases, persistent low-level inflammation etc.
My family also runs air purifiers in our main living room and our bedrooms. (We use the Dyson ones which have a sensor to tell you PM2.5, PM10, formaldehyde, volatile oxygen compounds etc). So together that basically covers at least 1/3 of the day. I also have one in my office, which covers another 1/3 or so. I think we can’t be “perfect” on this, but running a purifier in the room you sleep in seems like a no-brainer.
A story here in The Guardian about “healthy life expectancy” being in decline.
a child born this morning in Britain can expect to be in good health only until they are 61. The last 20 years of their life will be blighted by illness: dodgy hearts, painful joints, an inability to get about. Our healthy life expectancy has been dropping for years; it is now the lowest since 2011, when records began.
It seems that a huge part of it is economic. Poor living conditions, high stress.
The working-class suburb where I was raised, Edmonton, ranks among the most deprived in the country; the middle-class suburb where I currently live is among the least deprived. I could see them on her map, along with figures suggesting my two small daughters can expect almost a decade more of good health than girls living in my old home, just three miles away.
And the thing that (selfishly) worries me the most:
Scientists increasingly worry about “midlife mortality” in Britain: people in the prime of their lives dropping dead.
In Donald Trump’s America, where life expectancy is plunging, more women are dying between the ages of 25 and 44 than did in 1990.
So the red countries need to take statins and the purple need to take Rapamycin.
Or you could just be smart and take both. 
Ha, I think it’s more that we’ve made really good progress in preventing CVD. Statins and blood pressure medications work wonders. So if you deal with early deaths from CVD, you’ll end up with more deaths from other causes. And we aren’t anywhere near as good at preventing or curing cancers.
