Men and women in the prime of their lives are increasingly being diagnosed with serious cancers, including colorectal, breast, prostate, uterine, stomach (gastric), pancreatic, and more. One forecast predicts cancer for this age group will increase by 30% globally from 2019 to 2030.
MSK is a pioneer in caring for the specific needs of people facing what are often called early-onset cancers, who confront very different challenges than older adults. The coming surge in cases is a key reason MSK is building a new state-of-the-art hospital, called the MSK Pavilion.
Just as importantly, MSK experts are leading the investigation into why this is happening.
More Americans died from heat in 2023 than any year in over two decades of records, according to the findings published Monday. Last year was also the globe’s hottest year on record, the latest grim milestone in a warming trend fueled by climate change.
The study, published in the American Medical Association journal JAMA, found that 2,325 people died from heat in 2023. Researchers admit that number is likely an undercount. The research adjusted for a growing and aging U.S. population, and found the death toll was still staggering.
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Howard – along with researchers from the Uniformed Services University of the Health Sciences, in Maryland, and Pennsylvania State University – examined death certificate data between 1999 and 2023. Deaths were counted if heat was listed as an underlying or contributing cause of death.
Reported deaths remained relatively flat until around 2016, when the number of people dying began increasing, in what Howard, who studies health effects from extreme weather, calls a “hockey stick.” The hockey stick analogy has been used to describe warming global temperatures caused by climate change, where temperatures have swooped upward at alarming rates in recent years.
Howard’s study suggests the human toll follows the same outline. An important indicator is age-adjusted deaths per 100,000 people. That heat-related death rate has increased dramatically compared to the early 2000s, regardless of age or population size.
The upward trajectory appears to be sharpening recently. In 2022, 1,722 people died at an adjusted rate of 0.47. But 2023 saw 603 more deaths than the previous year, with an adjusted rate of 0.63, the highest on record.
Deaths weren’t evenly spread nationally. In an interview, Howard said deaths were overwhelmingly concentrated in traditionally hot regions: Arizona, California, Nevada and Texas.
The study is limited in how local governments classify heat-related deaths, which could mean the actual number of deaths is an undercount. It’s also potentially skewed as more people become aware of the fatal risks of heat. The study didn’t break down vulnerable groups. For example, people without air conditioning, those who live or work outdoors, and people with underlying health conditions, are all at greater risk of serious illness or death from heat.
Are we all really living longer? Let’s first point out that Princeton economists Anne Case and Angus Deaton, noted for their research in health and economics, recently showed that many Americans are not, in fact, enjoying extended lives. As they stated in their own New York Times op-ed, those without college degrees are “scarred by death and a staggeringly shorter life span.” According to their investigation, the expected lifespan for this group has been falling since 2010. By 2021, people without college degrees were expected to live to about 75, nearly 8.5 years shorter than their college-educated counterparts.
Overall life expectancy in America dropped in 2020 and 2021, with increases in mortality across the leading causes of death and among all ages, not just due to COVID-19. In August 2022, data confirmed that Americans are dying younger across all demographics. Again, the U.S. is an outlier. It was one of two developed countries where life expectancy did not bounce back in the second year of the pandemic.
So the argument that everyone is living longer greatly stretches the truth—unless, of course, you happen to be rich: A Harvard study revealed that the wealthiest Americans enjoy a life expectancy over a decade longer than their poorest counterparts.
Could the idea that working into our seventies and beyond boosts our health and well-being hold true? Obviously, for those in physically demanding roles, such as construction or mining, prolonged work is likely to lead to a higher risk of injury, accidents, and wearing down health-wise. But what about everybody else? What if you have a desk job? Wouldn’t it be great to get out there, do something meaningful, and interact with people, too?
Perhaps it’s easy for people like Steuerle and Kramon to imagine older people working in secure, dignified positions that might offer health benefits into old age – after all, those are the types of positions they know best.
But the reality is different. Economist Teresa Ghilarducci, a professor at the New School for Social Research, focuses on the economic security of older workers and flaws in U.S. retirement systems in her new book, Work, Retire, Repeat: The Uncertainty of Retirement in the New Economy. She calls those praising the health perks of working longer “oddballs” – those fortunate folks in cushy positions who have a lot of autonomy and purpose. Like lawmakers or tenured professors, for example.
Author(s): Lynn Parramore
Publication Date: 8 May 2024
Publication Site: Institute for New Economic Thinking
Compared to the general public, firefighters have a 9% higher rate of certain cancers, likely due to their exposure to high levels of carcinogens released into the air as buildings burn. The incidence of multiple myeloma — the first cancer Perez developed — is about 50% higher in firefighters than in the general population.
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Dr. C. Ola Landgren has been researching links between occupational exposures and multiple myeloma for a number of years — particularly in first responders such as firefighters. At Memorial Sloan Kettering Cancer Center in New York and the National Cancer Institute, Landgren began to recognize patterns.
In New York, for example, Landgren had three myeloma patients who lived on the same block on Staten Island. Their houses had been covered by dust after the World Trade Center towers fell in 2001.
“Myeloma has a precursor condition known as MGUS, which is more common in the population, allowing us to identify risks earlier,” Landgren said. “We’ve actually observed higher rates of MGUS in first responders compared to the general population.”
MGUS — which stands for monoclonal gammopathy of undetermined significance — has also been linked to pesticide use among farmers and exposure to Agent Orange among veterans of the Vietnam War. Levels also were higher in firefighters, police officers and construction workers who were on-site immediately after the 9/11 attacks.
In the experiment, he says, what if we compare the control arm of the Pfizer study against an imaginary vaccine arm. And for the thought experiment assume the vaccine is useless. As the table above shows, both groups have identical numbers of covid cases— just what you would expect from a useless vaccine. A straight forward analysis shows no benefit (second to last row)
But in the ‘fictional vaccine observational study’ cases are excluded for 36 days. When this is done the useless vaccine, looks like it reduces infections by 48%!!
Doshi makes a very good point in his paper that the solution is to subtract the 36 day infection rate from the observational control arm. Sadly most investigations don’t do that.
This is one of several biases Doshi discusses, and it plagues the vaccine literature.
Palo Alto’s [County, Iowa] 2022 tally of 842 farms generates nearly $800 million in annual market value. But nearly 400 small farms have been absorbed into bigger operations or otherwise stopped operating over recent decades, and Palo Alto’s population has dropped by 4,200 people since 1970.
Today’s Iowa farms are largely focused on raising hogs and growing corn, both of which are linked to numerous environmental problems. Farmers growing corn, for example, often rely heavily on applications of toxic pesticides and fertilizers, while livestock operations generate millions of tons of manure annually. The chemicals and manure pollute food and water consumed by people even far from farm fields.
When nitrogen from fertilizer and manure combine with oxygen they create nitrates, which routinely drain from farm fields into groundwater, streams, and rivers, contaminating water sources. Babies can suffer severe health problems when consuming nitrates in drinking water, and a growing body of literature indicates potential associations that include an increased risk of cancer. Exposure to elevated levels of nitrates in drinking water has been linked by researchers to cancers of the blood, brain, breast, bladder and ovaries.
As well, there are years of research showing that many herbicides and other pesticides applied to farm fields are linked to cancers and other diseases. The National Cancer Institute and the National Institute of Environmental Health Sciences have been funding research to investigate the links between disease and farming for more than 30 years, focusing their work on people in Iowa and North Carolina. Among the findings are links between pesticides and malignant brain tumors, multiple myeloma, pancreatic cancer and certain breast cancers.
Concerns about connections between the farm pollutants and cancer have been mounting, particularly in Palo Alto County, which had the highest incidence of cancer of any county in the state and the second-highest incidence of cancer among all US counties, with 83 new cases of cancer on average each year, in a population of 8,996, according to a 2023 report by US News.
Importance Many medical journals, including JAMA, restrict the use of causal language to the reporting of randomized clinical trials. Although well-conducted randomized clinical trials remain the preferred approach for answering causal questions, methods for observational studies have advanced such that causal interpretations of the results of well-conducted observational studies may be possible when strong assumptions hold. Furthermore, observational studies may be the only practical source of information for answering some questions about the causal effects of medical or policy interventions, can support the study of interventions in populations and settings that reflect practice, and can help identify interventions for further experimental investigation. Identifying opportunities for the appropriate use of causal language when describing observational studies is important for communication in medical journals.
Observations A structured approach to whether and how causal language may be used when describing observational studies would enhance the communication of research goals, support the assessment of assumptions and design and analytic choices, and allow for more clear and accurate interpretation of results. Building on the extensive literature on causal inference across diverse disciplines, we suggest a framework for observational studies that aim to provide evidence about the causal effects of interventions based on 6 core questions: what is the causal question; what quantity would, if known, answer the causal question; what is the study design; what causal assumptions are being made; how can the observed data be used to answer the causal question in principle and in practice; and is a causal interpretation of the analyses tenable?
Conclusions and Relevance Adoption of the proposed framework to identify when causal interpretation is appropriate in observational studies promises to facilitate better communication between authors, reviewers, editors, and readers. Practical implementation will require cooperation between editors, authors, and reviewers to operationalize the framework and evaluate its effect on the reporting of empirical research.
Disruptions in mental-health care during the pandemic left many Americans vulnerable. Among people ages 18 to 44, insurance claims related to psychotic episodes rose 30% to 2 million in 2023 from 2019, according to LexisNexis Risk Solutions, a data-analytics company. Around the U.S., hospitals are overwhelmed. Emergency rooms are adding security guards. Jails serve as a last resort for those unable to care for themselves.
Why women are at greater risk of autoimmune disease such as multiple sclerosis, lupus and rheumatoid arthritis is a long-standing medical mystery, and a team of researchers at Stanford University may now be a step closer to unraveling it.
How the female body handles its extra X chromosome (the male body has just one plus a Y chromosome) might be a factor that helps explain why women are more susceptible to these types of disorders, a new study has suggested. The predominantly chronic conditions involve an off-kilter immune system attacking its own cells and tissues.
While the research involving experiments on mice is preliminary, the observation, after further study, may help inform new treatments and ways to diagnose the diseases, said Dr. Howard Chang, seniorauthor of the paper published in the journal Cell on February 1.
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Other researchers had focused on the disorders’ “female bias” by analyzing sex hormones or chromosome counts. Chang instead zoned in on the role played by a molecule called Xist (pronounced exist) that is not present in male cells.
The Xist molecule’s main job is to deactivate the second female X chromosome in embryos, ensuring that the body’s cells don’t get a potentially toxic double whammy of the chromosome’s protein-coding genes.
“Xist is a very long RNA, 17,000 nucleotides long, or letters, and it associates with approximately almost 100 proteins,” Chang said. Xist molecules work with those proteins to shut down gene expression in the second X chromosome.
Importance Antivaccine sentiment is increasingly associated with conservative political positions. Republican-inclined states exhibit lower COVID-19 vaccination rates, but the association between political inclination and reported vaccine adverse events (AEs) is unexplored.
Objective To assess whether there is an association between state political inclination and the reporting rates of COVID-19 vaccine AEs.
Design, Setting, and Participants This cross-sectional study used the AE reports after COVID-19 vaccination from the Vaccine Adverse Event Reporting System (VAERS) database from 2020 to 2022, with reports after influenza vaccines from 2019 to 2022 used as a reference. These reports were examined against state-level percentage of Republican votes in the 2020 US presidential election.
Exposure State-level percentage of Republican votes in the 2020 US presidential election.
Main Outcomes and Measures Rates of any AE among COVID-19 vaccine recipients, rates of any severe AE among vaccine recipients, and the proportion of AEs reported as severe.
Results A total of 620 456 AE reports (mean [SD] age of vaccine recipients, 51.8 [17.6] years; 435 797 reports from women [70.2%]; a vaccine recipient could potentially file more than 1 report, so reports are not necessarily from unique individuals) for COVID-19 vaccination were identified from the VAERS database. Significant associations between state political inclination and state AE reporting were observed for all 3 outcomes: a 10% increase in Republican voting was associated with increased odds of AE reports (odds ratio [OR], 1.05; 95% CI, 1.05-1.05; P < .001), severe AE reports (OR, 1.25; 95% CI, 1.24-1.26; P < .001), and the proportion of AEs reported as severe (OR, 1.21; 95% CI, 1.20-1.22; P < .001). These associations were seen across all age strata in stratified analyses and were more pronounced among older subpopulations.
Conclusions and Relevance This cross-sectional study found that the more states were inclined to vote Republican, the more likely their vaccine recipients or their clinicians reported COVID-19 vaccine AEs. These results suggest that either the perception of vaccine AEs or the motivation to report them was associated with political inclination.
Now let’s turn to the paper. Here is what the authors find (weak correlation btw voting and vaccine injuries) , and here are the issues.
These data are ecological. It doesn’t prove that republicans themselves are more likely to report vaccine injuries. It would not be difficult to pair voting records with vaccine records at an individual patient level if the authors wished to do it right— another example of research laziness.
What if republicans actually DO have more vaccine injuries? The authors try to correct for the fact by adjusting for influenza adverse events.
Let me explain why this is a poor choice. The factors that predict whether someone has an adverse event to influenza vaccine may not be the same as those that predict adverse events from covid shots. It could be that there are actually more covid vaccine injuries in one group than another— even though both had equal rates of influenza injuries.
Another way to think of it is, there can be two groups of people and you can balance them by the rate with which they get headaches from drinking wine, but one group can be more likely to get headaches from reading without glasses because more people in that group wear glasses. In other words, states with more republicans might be states with specific co-morbidities that predict COVID vaccine adverse side effects but not influenza vaccine side effects. We already know that COVID vaccine injuries do affect different groups (young men, for e.g.).
Author(s): Vinay Prasad
Publication Date: 2 Apr 2024
Publication Site: Vinay Prasad’s Thoughts and Observations at substack
In this paper I use the 1973 cross-sectional Current Population Survey (CPS) matched to longitudinal Social Security administrative data (through 1998) to examine the relationship between retirement age and mortality for men who have lived to at least age 65 by year 1997 or earlier.1 Logistic regression results indicate that controlling for current age, year of birth, education, marital status in 1973, and race, men who retire early die sooner than men who retire at age 65 or older. A positive correlation between age of retirement and life expectancy may suggest that retirement age is correlated with health in the 1973 CPS; however, the 1973 CPS data do not provide the ability to test that hypothesis directly.
Regression results also indicate that the composition of the early retirement variable matters. I represent early retirees by four dummy variables representing age of entitlement to Social Security benefits—exactly age 62 to less than 62 years and 3 months (referred to as exactly age 62 in this paper), age 62 and 3 months to 62 and 11 months, age 63, and age 64. The reference variable is men taking benefits at age 65 or older. I find that men taking benefits at exactly age 62 have higher mortality risk than men taking benefits in any of the other four age groups. I also find that men taking benefits at age 62 and 3 months to 62 and 11 months, age 63, and age 64 have higher mortality risk than men taking benefits at age 65 or older. Estimates of mortality risk for “early” retirees are lowered when higher-risk age 62 retirees are combined with age 63 and age 64 retirees and when age 62 retirees are compared with a reference variable of age 63 and older retirees. Econometric models may benefit by classifying early retirees by single year of retirement age—or at least separating age 62 retirees from age 63 and age 64 retirees and age 63 and age 64 retirees from age 65 and older retirees—if single-year breakdowns are not possible.
The differential mortality literature clearly indicates that mortality risk is higher for low-educated males relative to high-educated males. If low-educated males tend to retire early in relatively greater numbers than high-educated males, higher mortality risk for such individuals due to low educational attainment would be added to the higher mortality risk I find for early retirees relative to that for normal retirees. Descriptive statistics for the 1973 CPS show that a greater proportion of age 65 retirees are college educated than age 62 retirees. In addition, a greater proportion of age 64 retirees are college educated than age 62 retirees, and a lesser proportion of age 64 retirees are college educated than age 65 or older retirees. Age 63 retirees are only slightly more educated than age 62 retirees.
Despite a trend toward early retirement over the birth cohorts in the 1973 CPS, I do not find a change in retirement age differentials over time. However, I do find a change in mortality risk by education over time. Such a change may result from the changing proportion of individuals in each education category over time, a trend toward increasing mortality differentials by socioeconomic status, or a combination of the two.
This paper does not directly explore why a positive correlation between retirement age and survival probability exists. One possibility is that men who retire early are relatively less healthy than men who retire later and that these poorer health characteristics lead to earlier deaths. One can interpret this hypothesis with a “quasidisability” explanation and a benefit optimization explanation. Links between these interpretations and my analysis of the 1973 CPS are fairly speculative because I do not have the appropriate variables needed to test these interpretations.
A quasi-disability explanation, following Kingson (1982), Packard (1985), and Leonesio, Vaughan, and Wixon (2000), could be that a subgroup of workers who choose to take retired-worker benefits at age 62 is significantly less healthy than other workers but unable to qualify for disabled-worker benefits. An econometric model with a mix of both these borderline individuals and healthy individuals retiring at age 62 and with almost no borderline individuals retiring at age 65 could lead to a positive correlation between retirement and mortality, even if a greater percentage of individuals who retire at age 62 are healthy than unhealthy. Evidence for this hypothesis can be inferred from the finding that retiring at exactly age 62 increases the odds of dying in a unit age interval by 12 percent relative to men retiring at 62 and 3 months to 62 and 11 months for men in the 1973 CPS. In addition, retiring exactly at age 62 increases the odds of dying by 23 percent relative to men retiring at age 63 and by 24 percent relative to men retiring at age 64. A group with relatively severe health problems waiting for their 62nd birthday to take benefits could create this result.
An explanation based on benefit optimization follows Hurd and McGarry’s research (1995, 1997) in which they find that individuals’ subjective survival probabilities roughly predict actual survival. If men in the 1973 CPS choose age of benefit receipt based on expectations of their own life expectancy, then perhaps a positive correlation between age of retirement and life expectancy implies that their expectations are correct on average. If actuarial reductions for retirement before the normal retirement age are linked to average life expectancy and an individual’s life expectancy is below average, it may be rational for that individual to retire before the normal retirement age. Evidence for this hypothesis can be inferred from the fact that men retiring at age 62 and 3 months to age 62 and 11 months, age 63, and age 64 all experience greater mortality risk than men retiring at age 65 or older. If only men with severe health problems who are unable to qualify for disability benefits are driving the results, we probably would not expect to see this result. We might expect most of these individuals to retire at the earliest opportunity (exactly age 62).2
Author(s): Hilary Waldron
Publication Date: August 2001
Publication Site: Social Security Office of Policy, ORES Working Paper No 93
