Category Archives: Transhuman News

People are living longer, and organizations are shifting their attitudes toward older workers as a result. Organizations that can turn advancing worker age into an asset could gain a competitive advantage.

Rising life expectancies and an aging global workforce present organizations with unprecedented challenges and untapped opportunities. Companies that plan, design, and experiment with workforce strategies, workplace policies, and management approaches for longer working lives can reap a longevity dividend. Those that lag behind face potential liability concerns and skill gaps. Creating ways for people to have meaningful, productive multi-stage and multidimensional careers is a major opportunity to engage workers across generations.

One of modern sciences greatest achievements is longevity: the unprecedented length of human lives today. Average global life expectancy has rocketed from 53 years in 1960 to 72 years in 2015and it is still climbing,1 with life expectancy projected to grow by 1.5 years per decade.2 Longevity, combined with falling birth rates, is dramatically increasing the share of older people in populations worldwide.3 Looking ahead, the number of retirees per worker globally is expected to decline from 8:1 today to 4:1 in 2050.4

These demographic facts have profound implications for individuals, organizations, and society. In this era of longevity, an individuals career can last far longer, spanning generations of technologies and businesses. Companies can employ people into their 60s, 70s, and beyond as the pool of traditional working-age (20- to 54-year-old) adults shrinks. For their part, many individuals find the needfinancially and/or emotionallyto stay in the workforce past traditional retirement age.

In our 2018 Global Human Capital Trends survey, 29 percent of therespondents rated longevity as a very important issue, and another 40 percent rated it as important. Respondents in Japan in particular, whose population is rapidly aging, were especially concerned about the issue, with 41 percent saying that it is very important.

Population aging poses a workforce dilemma for both economies and organizations. Thirteen countries are expected to have super-aged populationswhere more than one in five people is 65 or olderby 2020, up from just three in 2014.5 These include major economies such as the United States, the United Kingdom, Japan, Germany, France, and South Korea. Chinas 65-and-older population is projected to more than triple from approximately 100 million in 2005 to over 329 million in 2050.6 In fact, analysts have estimated that 60 percent of the worlds population over 65 will live in Asia by 2030.7

Compounding the challenge, almost all developed economies now have birth rates below the replacement rate of 2.1.8 This means that companies in these countries must either attract workers from abroad or tap into the maturing workforce. For a view of the challenges ahead, one needs look no further than Japanthe worlds oldest countrywhere a shortage of roughly 1 million employees in 2015 and 2016 is estimated to cost nearly $90 billion.9

New research is being conducted to help organizations shape their talent and business strategies for an era of longevity. The MIT AgeLab, for example, works with businesses, government, and other stakeholders to develop solutions and policies aimed at engaging the elderly population. The AgeLab uses consumer-centered thinking to understand the challenges and opportunities of longevity in order to catalyze innovation across business markets.10

As talent markets grow more competitive, organizations often find it valuable to keep older workers on the job rather than replace them with younger ones. Our research shows that older workers represent a largely untapped opportunity: Only 18 percent of this years respondents said that age is viewed as an advantage in their organization. But leading companies are beginning to focus on this talent pool as a competitive advantage.

The older labor pool represents a proven, committed, and diverse set of workers. More than 80 percent of US employers believe that workers aged 50 and more are a valuable resource for training and mentoring, an important source of institutional knowledge, and offer more knowledge, wisdom, and life experience.11 The UK government incentivizes employers to retain, retrain, and recruit older workers, and it is committed to policies that support lifetime learning and training and decrease loneliness and social isolation.12

Proactive organizations are tapping into the older talent pool by extending their career models, creating new development paths, and inventing roles to accommodate workers in their 50s, 60s, and 70s. This year, 16 percent of therespondents we surveyed for this report say their companies are creating special roles for older workers, and 20 percent are partnering with older workers to develop new career models. Organizations could find great value in older workers ability to serve as mentors, coaches, or experts. Taking on these kinds of roles allows older workers to pass the baton to younger generations, while making room for ambitious younger workers.

Many companies are also experimenting with workplace changes to help older employees remain in the workforce. For instance, BMW increased productivity on an assembly line staffed with older workers by 7 percent in just three months through simple changes such as providing cushioned floors and adjustable work benches.13 Home Depot and other organizations are engaging older workers with flexible scheduling options and part-time positions.14 Further, as many as one-third of retirees are willing to work part-time, offering opportunities to leverage this group on a contingent or gig basis.15

Reskilling also plays a role in successful strategies to utilize older talent. One global telecommunications provider encourages senior workers to reinvent themselves and invests in programs to help them acquire new technical skills.16 Software engineers who have built careers on older technologies such as COBOL or C++ can use this experience to learn mobile computing, AI, and other technologies at a very rapid rate.

An interesting and little-known fact, moreover, is that older people are among the most entrepreneurial of workers across age groups. Between 1996 and 2014, the percentage of older workers (aged 5564) starting new ventures increasedexceeding (by 68 percent) the rate of entrepreneurship among millennial entrepreneurs (aged 2034), which actually decreased during the same period.17

The transition toward older talent can present challenges. Older workers may have specialized workplace needs and can attract resentment from younger workers, and they often enjoy higher salaries because of their tenure. Organizations looking to assimilate an older worker population may face the need to design new wage policies, create more flexible rewards programs, and train young leaders to manage people across generations (including team members who may be their parents age).

Pensions are another area where longevity impacts organizations. The World Economic Forum estimates that a $70 trillion global retirement savings gap exists today, highlighting the sharp difference between retirement needs and actual retirement income. Moreover, this gap is projected to grow to $400 trillion by 2050.18 Helping older adults to work longer and manage their retirement savings will be a vital need for companies in order to avoid the negative productivity effects of financial stress.

Our Global Human Capital Trends research shows that many organizations are unprepared to deal with the aging of global workforces. Nearly half of the respondents we surveyed (49 percent) reported that their organizations have done nothing to help older workers find new careers as they age. Rather than seeing opportunity, 20 percent of respondents view older workers as a competitive disadvantage, and in countries such as Singapore, the Netherlands, and Russia, this percentage is far higher. In fact, 15 percent of respondents believed that older employees are an impediment to rising talent by getting in the way of up-and-coming younger workers.

Perceptions of workers over 55 years old spanned both extremes, though these perceptions varied significantly by country.

Explore the data further in the Global Human Capital Trends app.

Based on these findings and our anecdotal observations, we believe there may be a significant hidden problem of age bias in the workforce today. Left unaddressed, perceptions that a companys culture and employment practices suffer from age bias could damage its brand and social capital.

Age discrimination is already becoming a mainstream diversity issue and liability concern. More than 21,000 age discrimination complaints were filed with the US Equal Employment Opportunity Commission in 2016.19 The problem is particularly acute in Silicon Valleys technology industry, where older software engineers are often pushed to take lower-paying jobs or look for work outside Silicon Valley because of the emphasis on the youth culture.20

The demographic math is undeniable: As national populations age, challenges related to engaging and managing the older workforce will intensify. Companies that ignore or resist them may not only incur reputational damage and possible liabilities, but also risk falling behind those organizations that succeed in turning longevity into a competitive advantage.

Staying competitive in a world of unprecedented longevity demands that organizations adopt new strategies to engage with older talent. Traditional assumptionsthat learning ends in ones 20s, career progression ends in the 40s, and work ends in the 60sare no longer accurate or sustainable. Rethinking workforce strategies across multiple generations to account for longer lives will require open minds and fresh approaches.

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The longevity dividend: Work in an era of 100-year lives

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Our lifespan or more importantly our health span, as discussed during GENs recent The State of Biotech summit, is a complex quantitative parameter influenced by our genes, cells, physiology, and environment. Knowing the genes that affect longevity is an important step that could inform the development of treatments, the practice of precision medicine, and potentially extend human health span. However, it has been challenging to identify genetic determinants of longevity due to the lack of integrated approaches that leverage multiple lines of evidence linked to complex traits.

A new collaborative study published in the journal Science, identified genes that influence longevity in a sex- and age-specific manner. The insights from the study open doors for hypothesis-driven studies on therapies for aging and age-related diseases.

Maroun Bou Sleiman, PhD, a scientist at the laboratory of integrative systems physiology at EPFL, Switzerland, and Suheeta Roy, PhD, an assistant professor at the University of Tennessee Health Science Center (UTHSC), are co-lead authors of the study, while Robert Williams, PhD, professor of genetics, genomics, and informatics at UTHSC and Johan Auwerx, PhD, professor of integrative systems physiology at EPFL are co-senior authors of the study.

This is the largest study of the genetics of normal variation of lifespan in a single huge mouse family called the UM-HET3 (more than 3000 progeny), said Williams. We discovered a small number of chromosomal regions that modulate lifespan both early and late in life. We then developed general resources for those interested in specific genes that may modulate differencesin lifespan both as a function of sex and age.

The large-scale, multicenter study analyzed DNA variants in 3276 UM-HET3 micea genetically diverse mouse model used in aging intervention studies such as the National Institute on Agings Interventions Testing Program (NIA ITP).

In a Perspective article published in the same issue of the journal, Joo Pedro de Magalhes, PhD, a professor of molecular biogerontology at the University of Birmingham noted that although earlier studies have identified over 2000 longevity-linked genes in model organisms, One underappreciated limitation of such studies is that they are mostly conducted in inbred, genetically homogeneous animal populations. This means that discoveries in the genetics of aging, as well as dietary and pharmacological manipulations, may be strain-specific because there could be genetic background effects. The use of M-HET3 mice in the current study overcomes this limitation.

The investigators analyzed changes in liver gene expression with age and genotype, in mice from the same genetic cross to identify genetic loci for further investigation.

We interrogated whether the genetic basis of longevity is sex- and age-dependent, and whether nongenetic factors such as litter size and the effect of early access to nutrients on growth contribute to longevity determination, the authors noted.

When the researchers analyzed male and female genetic datasets jointly, they identified a region of chromosome 12 linked to longevity that was previously reported. However, when they analyzed the male and female datasets separately, they found a single locus on chromosome 3 linked to longevity in females. Longevity loci in male mice could be detected only when early deaths were eliminated from the dataset. This indicated that in males, some genetic determinants affected longevity only beyond a certain age.

The researchers also found, access to nutrients early in life affected growth and thereby was associated with body weight, litter size, and longevity. Using Mendelian randomization, the scientists recapitulated the links between early development, adult weight, and longevity in humans.

Comparing gene expression in the liver, the authors found higher interferon-related gene expression in female mice, and higher immune-related gene expressions in old mice. They then combined their mouse results with data from other model organisms and humans to compile a score-based prioritized list of genes linked to longevity.

Finally, the authors validated five high-scoring, conserved longevity genes by conducting life-span experiments in the microscopic worm Caenorhabditis elegans which normally lives for about three weeks. These include the protein kinases Hipk1 and Pdk1, a gycosyltransferase, Ddost, a heparan sulfate proteoglycan, Hspg2, and a zinc finger protein linked to vascular disease, Fgd6.

We have uncovered a handful of loci in this study and many candidate genes that are high priority for downstream analyses, said Williams. But by expanding the sample size five times, we would be able to detect roughly 10 to 20 times as many loci and many of these loci would be mapped with much higher positional precision. This would improve the efficiency of subsequent analyses of mechanisms that modulate lifespan and longevity.

Because longevity is a complex, multifactorial phenotype, it will also be important to elucidate in the future which processes and diseases are affected by genetic variants associated with longevity, noted de Magalhes.

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Clues to Human Longevity Unearthed in Largescale Mouse Genetic Study - Genetic Engineering & Biotechnology News

But to test the same treatments in people, wed need to run clinical trials for decades, which would be very difficult and extremely expensive. So the hunt is on for chemical clues in the blood or cells that might reveal how quickly a person is aging. Quite a few aging clocks, which purport to give a persons biological age rather than their chronological age, have been developed. But none are reliable enough to test anti-aging drugsyet.

As I leave to head back to my own slightly less posh but still beautiful hotel, Im handed a gift bag. Its loaded up with anti-aging supplements, a box with a note saying it contains an AI longevity assistant, and even a regenerative toothpaste. At first glance, I have absolutely no idea if any of them are based on solid science. They might be nothing more than placebos.

Ultimately, of all the supplements, drugs and various treatments being promoted here, the workout is the one thats most likely to work, judging from the evidence we have so far. Its obvious, but regular exercise is key to gaining healthy years of life. Workouts designed to strengthen our muscles seem to be particularly beneficial for keeping us healthy, especially in later life. They can even help keep our brains young.Ill be penning a proper write up of the conference when Im back home, so if your curiosity has been piqued, keep an eye out for that next week! In the meantime, heres some related reading:

An experimental Alzheimers drug appears to slow cognitive decline. Its huge news, given the decades of failed attempts to treat the disease. But the full details of the study have not yet been published, and it is difficult to know how much of an impact the drug might have on the lives of people with the disease. (STAT)

Bionic pancreases could successfully treat type 1 diabetes, according to the results of a clinical trial. The credit card-sized device, worn on the abdomen, can constantly monitor a persons blood sugar levels, and deliver insulin when needed. (MIT Technology Review)

Were headed for a dementia epidemic in US prisons. Theres a growing number of older inmates, and the US penal system doesnt have the resources to look after them. (Scientific American)

Unvaccinated people are 14 times more likely to develop monkeypox disease than those who receive the Jynneos vaccine are, according to the US Centers for Disease Control and Prevention. But the organization doesnt yet know how the vaccine affects the severity of disease in those who do become unwell, or if there is any difference in protection for people who are given fractional doses. (The New York Times $)

Dont call them minibrains! In last weeks Checkup, I covered organoidstiny clumps of cells meant to mimic full-grown organs. Theyve mainly been used for research, but weve started to implant them into animals to treat disease, and humans are next. Arguably the best-known organoids are those made from brain cells, which have been referred to as minibrains. A group of leading scientists in the field say this wrongly implies that the cells are capable of complex mental functions, like the ability to think or feel pain. They ask that we use the less-catchy but more accurate term neural organoid instead. (Nature)

That's it for this week. Thanks for reading!

Jess

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Can we find ways to live beyond 100? Millionaires are betting on it. - MIT Technology Review

New research suggests that moderate caloric restriction in humans has benefits beyond weight loss. In a two-year study, researchers saw improved immune function and T cell production, and a reduction in inflammation in participants who reduced their calories by about 14 percent.

Caloric restriction (CR) has been an important topic in aging and longevity research for many years. Weve learned from studies on many types of animalsfrom flies to mice to nonhuman primatesthat moderate CR without malnutrition prolongs lifespan, slows biological aging, and delays the development of chronic diseases.

More recent research has tried to understand the biology behind the beneficial, longevity-promoting effects of CR, and how it could be used to improve human health. The Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE) trial was the first CR trial conducted in healthy humans. Participants in the CR group were instructed to reduce calorie intake moderately (a goal of 20 percent) for two years.

Previous results from the CALERIE trial suggested moderate CR reduced fat mass, improved insulin sensitivity, reduced inflammatory markers, and improved cardiovascular risk biomarkers.

A new study from the CALERIE trial investigated immune function and gene expression in fat tissue in participants who restricted calories by an average of 14 percent for 2 years.

Some research in animals had suggested that CR could impair immunity. However, these studies usually reduced calories more dramatically, by about 40 percent. These animals lived longer, on average, than control animals but were more susceptible to infection. This suggests that a 40 percent calorie reduction led to insufficient resources for the immune system. Moderate CR of 14 percent, however, in the CALERIE trial, showed signs of improved immune function in the newly published study.

The researchers chose to analyze the thymus, where T cells (a subset of immune cells) mature, in CALERIE participants, because aging of the thymus begins earlier than other organs. Starting in middle age, the thymus begins to shrink, accumulate fat, and release fewer T cells, reducing the capacity for immune surveillance.

Using MRI and indicators of T cell abundance in the blood, the researchers determined that the thymus glands in the CR participants were larger and less fatty, and were releasing more T cells after two years than they were at the beginning of the study, whereas the control group showed no change.

Since excess fat tissue drives inflammation and inflammation drives aging, the researchers also investigated gene expression in adipose (fat) tissue at baseline, one year, and two years of caloric restriction. They found increases in the expression of 233 genes and decreases in 131. Several of the largest gene expression changes were indicative of a lower level of inflammation.

They focused on one particular gene: the platelet-activating factor acetylhydrolase (PLA2G7), whose expression was decreased in response to CR. Little is known about PLA2G7 so far. However, higher circulating levels of PLA2G7 have been linked to inflammation-related diseases such as cardiovascular disease, autoimmune disease, and Type 2 diabetes.

They investigated PLA2G7 further by deleting the gene in mice, and found lower circulating proinflammatory cytokines, reduced inflammation in fat tissue, limited weight gain, and maintenance of the volume of the thymus compared to control animals. These results are consistent with improved immune health and lower inflammation, and were similar to the results in humans under moderate CR, suggesting PLA2G7 is an important gene underlying the benefits of CR.

Overall, the findings from this study suggest that moderate caloric restriction alters gene expression to promote immune function and reduce inflammation, strengthening the evidence that moderate caloric restriction in the context of micronutrient excellence extends life span.

I developed the nutritarian diet,a plant-based, nutrient-dense diet, as a powerful way to reverse chronic disease, strengthen immune defenses, and slow the aging process. Its unique in that it pays attention to comprehensive micronutrient adequacy using a wide variety of nutrient-rich foods along with a judicious use of supplements (such as DHA and EPA omega-3 fatty acids, vitamins B12 and K2, zinc, and iodine) to prevent any insufficiencies from reducing or eliminating animal products. This nutritarian approach lowers the instinctual drive for calories, allowing people to be satisfied with fewercalories and enjoy eating more.

Sources:Aging and Caloric Restriction Research: A Biological Perspective With Translational Potential

Caloric Restriction in Humans Reveals Immunometabolic Regulators of Health Span

A 2-Year Randomized Controlled Trial of Human Caloric Restriction: Feasibility and Effects on Predictors of Health Span and Longevity

Calorie Restriction Enhances T-Cell-Mediated Immune Response in Adult Overweight Men and Women

Body-Composition Changes in the Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE)-2 Study: A 2-y Randomized Controlled Trial of Calorie Restriction in Nonobese Humans

2 Years of Calorie Restriction and Cardiometabolic Risk (CALERIE): Exploratory Outcomes of a Multicentre, Phase 2, Randomised Controlled Trial

Caloric RestrictionHas a New Player

Caloric Restriction in Humans Reveals Immunometabolic Regulators of Health Span

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Restrict Calories to Boost Immune Function - The Epoch Times

In 1899, W.E.B. Du Bois published The Philadelphia Negro, a first-of-its-kind sociological case study of a Black community, combining urban ethnography, social history, and descriptive statistics. Its novel use of data to identify racial inequity undoubtedly influenced Du Bois vision for the NAACP, which he would go on to help found, as an organization that uses empirical evidence and facts in its efforts to dismantle injustice.

In the spirit of Du Bois and others who have pursued truth and justice, the NAACP and the Brookings Institution have partnered to develop tools and resources that will empower communities with data and information. The partnerships primary project is the Black Progress Index, which provides a means to understand the health and well-being of Black people and the conditions that shape their lives.

The Black Progress Index will evolve over the course of the partnership, but its first step is to find the places where Black people are thriving most, as measured through the social predictors of life expectancy at birth. In other words, the Black Progress Index identifies and measures the social conditions that predict long and healthy lives for Black Americans.

We chose to focus on the social conditions that predict life expectancy because they are a cumulative measure of health and well-being, summarizing many biological and non-biological influences on our lives. People tend to live longer in places where they evaluate their lives positively and enjoy excellent physical and mental health. Unlike other summary measures of well-being and health, life expectancy can be readily analyzed using the same data and methods across most U.S. counties and metropolitan areas.

We highlight the areas where Black people have been living the longest because it may provide insight into the local civic actions that have produced those outcomesactions that other places may take. Each year, we will add additional focal points of well-being, building out a comprehensive examination of the living conditions of Black people.

To emphasize Black health is not to de-emphasize social inequity. The legacy of structural racism pervades the country in the form of lower wealth and socioeconomic status for Black people. In turn, this legacy influences the so-called social determinants of health, which we define as patterns of behavior and environmental conditions that have largely social causes, but also biological implications on mental and physical health. Relatively low levels of college completion, low wealth, and high exposure to violent crime are especially relevant examples of these social determinants.

A goal of this research is to identify which social factors are the most important, provide evidence on the size of their effects, and track the places that do better or worse on these factors, as well as the places that over- or under-perform relative to predictions. There may be valuable lessons from the people and organizations in places that have better outcomes than expected.[1]

While we focus on life expectancy, our research is also relevant to quality of life more broadly. Using large sample microdata from Gallup and Sharecare, we foundnot surprisinglythat Black people evaluate their lives more positively in places (measured as counties) with higher Black life expectancy. This data was not available at the county level for much of the country, so we focus on life expectancy to provide detailed geographic information. Beyond subjective well-being, we also examined other objective measures of health, including age-adjusted mortality and the share of children born at low birthweight. This analysis confirms that the factors identified in the Index are predictive in explaining these outcomes too.

In addition, the Index can be de-composed into the component parts that were shown to be most impactful on life expectancy: wealth, human and social capital (e.g., education, social networks, religion), environmental quality, safety, and family. Our hope is that understanding how these factors play out across local areas and neighborhoods can help communities take collective action and tailor policy to fit their needs.

The vast gulfs in Black life expectancy across the U.S.

In Manassas Park, Va. and Weld County, Colo., the mean life expectancy for Black residents is 96a national high. Yet in Jefferson County, Ohio, the average Black person lives 33 fewer years. That gap is roughly equivalent to 100 years of progress in living standards, medical science, and public health.

Using 13 variables chosen through a rigorous process of machine-learning and expert judgment, the Black Progress Index can explain over half of the variation in Black life expectancy across counties. The 13 indicators fall into five categories, as follows:

The top-performing counties across these 13 indicators include Cumberland County in the Portland, Maine metro area; Loudon, Fairfax, Prince William, and Montgomery counties, all outside of Washington, D.C.; Collier County in the Naples, Fla. metro area; Rockingham County, N.H., outside of Boston, and Snohomish County, Wash., near Seattle. The 20 counties with the highest Black Progress Index scores are reported in Table 1 (see Appendix Table 1 for a corresponding list of metropolitan areas and for the full list of counties as well as their population counts,click here).

In Loudon and Rockingham counties, actual life expectancy almost exactly matches the Indexs predicted life expectancy. For Cumberland County, actual life expectancy is three years shorter than predicted, and in Collier County, it is three years longer. We believe further investigation may uncover useful explanations for why the former under-performs and the latter over-performs.

Table 1. The top 20 U.S. counties with highest Black Progress Index score, actual life expectancy, and life years unexplained by model

For every county and metropolitan area in our database, we decompose the Black Progress Index into the various contributions of each of the 13 factors in our model and an unexplained (residual) component. To illustrate, consider the largest county: Montgomery County, Md. Ranking each factor by its contribution to the Index shows that the very high share of foreign-born Black adults in the area predicts an additional 3.3 years of life expectancy, making it the largest contributor to the areas high score. This is because the foreign-born share has a large average effect across counties and is very large locally (three standard deviations above the mean). The countys low rate of gun violence adds 1.3 years to life expectancy, and its high levels of college education and median household income add an additional year each. The countys Black students test scores are slightly below average, but not low enough to predict a large drop in life expectancy.

Table 2. Contribution of social determinants of health to Black Progress Index in Montgomery County, Md.

Methodology for county-level analysis

Life expectancy varies considerably across racial groups in the United States. Life expectancy at birth for Black people is 74.8, which is lower than all major race and ethnic groups except American Indian and Alaska Natives (71.8). Non-Hispanic white Americans have a life expectancy of 78.8, while Latino or Hispanic and Asian American life expectancies are 81.9 and 85.6, respectively.[5]

Differences in the causes of deathas listed on death recordsshed light on these disparities.[6] Among the leading causes of the life expectancy gap between Black people and other groups, several causes are loosely connected, if at all, to biological health: accidents and unintentional deaths as well as assault and homicide. These can be thought of as largely social in origin. Likewise, even explicitly biological causes of death have social aspects related to health behaviors, prevention, and treatment. These facts motivate our effort to focus on social factors that predict health and longevity for Black Americans.

Our main goal is to predict county-level Black life expectancy at birth, using 2018-2020 data from the University of Wisconsins County Health Rankings and Roadmaps program. Life expectancy is a clear and useful measure of longevity, but it is strongly affected by deaths at a young age, which result in more years of lost potential life.

Our analysis preceded in three stages. First, our discovery stage involved downloading and processing hundreds of variables from a variety of data sources, including the U.S. Census Bureau, Internal Revenue Service, the Federal Reserve, Facebook, Redfin, the U.S. Congress Joint Economic Committees Social Capital Project, the County Health Rankings and Roadmaps program, and the Centers for Disease Control and Prevention.

In stage two, we ran these variables through a common machine-learning algorithm (Lasso) to select variables and rank variable importance, using life expectancy at birth and age-adjusted mortality as the target outcomes. This process eliminates much of the subjective bias associated with model selection and allows for unexpected variables to rise to the top (such as the share of the Black population that was foreign-born). The downside of this approach is that a nave Lasso model is atheoretical and can lead to suboptimal combination of variables in the presence of multicollinearity. In other words, two variables that closely measure the same constructor are highly correlated because they share an underlying causal pathwaymay cancel each other out if included in the same model, or one or both may appear insignificant if included alongside a variable that is highly correlated with it. This can be true even if they have important causal effects on the outcome.

In stage three, we categorized the variables Lasso selected into distinct constructs. Then, we re-ran models with a smaller range of possible variables to reflect the best candidates within each family of constructs. For example, we didnt need three measures of family structure (the percentage of tax filers who are single, the percentage of Black children who do not live with their father, and the share of Black loans going to single borrowers), so we selected the best-performing measure of this group. Performance was judged based on county data coverage and related data quality issues, the absolute value of the t-statistic, and how the inclusion of the variable affects other variables that might be highly correlated with it.

Our final list of variables comes very close to maximizing adjusted R-squared, while preserving constructs that were consistently important in various iterations of the model. In the end, this is a subjective process that involved expert judgment, but was informed by machine learning. In future work, we will refine this list. Many constructs were tested and ultimately rejected in the final model because they did not add explanatory power in the presence of other variables chosen. These included racial segregation, access to health care, the percentage of residents with insurance, measures of household debt, median length of commuting times, access to green space, walkability, and access to grocery stores. This result does not mean that these and other rejected constructs do not have direct or indirect effects on health or Black life expectancy. We suspect that they were rejected because of their high correlation with more predictive variables, often closely related.

This process led to 13 variables, summarized below. The categories they fall into are environmental quality, family health, human and social capital, safety, and wealth.

Table 3. List of variables included in the final Index

The last step of our analysis was to use the selected variables to predict Black life expectancy at the county level using linear regression. Each variable is significant in the direction predicted by theory, and together, they explain 55% of the variation in Black life expectancy.

Thus, the Black Progress Index predicts Black life expectancy based on 13 underlying factors. In calculating the mean for a given geography, the factors are weighted according to the model by how well they predict Black life expectancy. The residual from this model is then used to calculate unexpected years of lifepositive for areas that over-perform relative to the Index, negative for those that under-perform, and approximately zero for areas that perform as predicted. This residual can be thought of as quantifying something unmeasured by the Index, which will be subject to future research.

To assess the robustness of our model, we varied the outcomes and sample and found it performed well in different samples and using different outcomes.

Specifically, we segmented the sample of counties into 423 rural counties (defined as non-metropolitan) and 814 metropolitan counties, and ran our model separately with each. The adjusted R-squared was 0.43 in the rural counties and 0.53 in the metropolitan counties. The better performance in metropolitan counties may be a reflection of underlying causal differences or may be the result of a larger measurement error in the underlying death records or population data.

In varying the outcomes, we conducted our regression analysis using age-adjusted mortality for Black people and the percentage of Black children born at low birthweight. The first is defined as the percentage of Black people who died in each county between 2016 and 2020 using data from the Centers for Disease Control and Prevention. Mortality rates treat each death equally, and with age-adjustment, they are not affected by age differences across communities. Age-adjusted mortality rates are less sensitive to deaths at young ages compared to life expectancy.

Our second outcome of interest is the percentage of Black children born at low birthweight (less than 5.5 pounds) using 2014-2020 data from the County Health Rankings and Roadmaps program. This measure accounts for the fact that death is not the only important measure of health; we are also interested in morbidity, but in the absence of a comprehensive measure of morbidity at the county level, we chose the share of Black children born at low birthweight. This outcome is a sign of poor maternal health and health care, and thus picks up on many potential issues related to morbidity.

We predicted age-adjusted mortality and low birthweight percentages using the same 13 items from our Index, and obtained similar results as when we used life expectancy. The adjusted R-squared values were only modestly smaller than in the primary model (0.46 for age-adjusted mortality and 0.36 for low-weight births).

Moreover, where the Black Progress Index is higher, the life expectancy of other groups is also higher. Our model explains 58% of the variation in non-Hispanic white life expectancy.

Given these results, we therefore conclude that our Index variables capture social conditions that are broadly relevant to health outcomes and meaningful both in rural and urban areas.

To assess the effects from each Index component, we standardized the measures so that one unit is equal to a standard deviation. This is a useful way to assess how a meaningful change in the variable would predict health. Here, we focus on life expectancy, since it has the clearest interpretation and forms the basis of our Index.

Of the 13 Index components, the percent of Black adults born outside the United States has the largest effect. One standard deviation in this variable (about 11 ppt with a mean of 7%) adds one year to predicted life expectancy for Black people living in the county. The causal interpretation is unclear; it may be a pure composition effect, in that foreign-born Black Americans enjoy better health than the native Black population. It is well established that foreign-born Black immigrants to the United States live longer than native-born Black Americans, and the gap is strikingly large: eight years for women and 10 years for men.[7] The gap remains even among Black adults on Medicare, suggesting that health insurance does not explain it.[8] Another possibility is that foreign-born Black Americans move to counties that have other advantages associated with health.

To provide some examples, in Cass County, N.D., which is in the Fargo metro area, 73% of the Black population is foreign-born and Black life expectancy reaches 78.6. In Scott County, Minn., which is in the Minneapolis metro area, 63% of the Black population is foreign-born and life expectancy reaches 89.7 years.

On the opposite end, many counties in the South have no foreign-born Black people, according to census data. One such county is Chester County, S.C., outside of the Charlotte, N.C. metropolitan area, where life expectancy for Black people is just 69.3 years.

The percentage of Black adults ages 25 and over with at least a bachelors degree is also highly predictive of longer life, adding 0.38 years for every standard deviation (11 ppt with a mean of 16%). The individual effect of education on health is well established, and living near higher-income adults may boost health in other ways, such as by improving markets, safety, or government policy and resources.[9]

The Black college attainment rate is very high in several counties in the Atlanta, Baltimore, and Washington, D.C. metro areas, including Forsyth County, Ga. (56%); Howard County, Md. (54%); and Arlington and Loudoun counties, Va. (51% and 50%, respectively). Life expectancy for Black adults in these places is also very high, ranging from 79.4 in Howard County to 82.4 in Loudoun County. On the opposite end, the Black college attainment rate is just 4.4% in Baker County, Fla., outside of Jacksonville, and Black life expectancy there is 76.4. Butts County, Ga., outside of Atlanta, has the same low Black college attainment rate and even lower Black life expectancy, at 73.8.

Black entrepreneurshipmeasured by the rate of business ownershipis a relatively small but still significant predictor of life expectancy. Roughly 1% of Black adults ages 18 to 64 own an employer business, and a standard deviation in ownership rates predicts an increase of roughly 0.2 years in life. The Black ownership rate is as high as 4% in Hidalgo County, Texas, where Black life expectancy is 91.5 years.

Overall, a standard deviation in each wealth measure adds 1.4 years of life. The same effect is 2.1 for human and social capital measures, 0.33 for environmental quality measures, 0.36 for family health measures, and 1.1 for safety measures.Black people live approximately 14 years longer in the counties ranked in the top 1% of the Index compared to counties at the bottom81.72 years versus 67.8 years.

Uncertainty remains about how variables influence life expectancy

The primary goal of this research is to find the social and neighborhood conditions of places where Black health is thriving. A better understanding of these social factors and how they vary across places can inform cooperative efforts to improve life prospects. Yet, the causal pathway linking these factors to life expectancy is not necessarily straightforward or clear from existing research, and more work will need to be done.

Take our measure of family health. In the average county in our sample, 57% of Black children are not living with their father, according to Census Bureau data. This matters for several reasons, but one is straightforward: When they are living in the household, Black fathers invest heavily in their children in terms of play, reading, helping with homework, and other activities. They spend much less time on these activities when they are not living in the household.[10]

Controlling for their living arrangements, Black fathers spend at least as much time as non-Hispanic white fathers do on these activities. But Black fathers are more than twice as likely to live apart from their children as non-Hispanic white fathers, so the overall effect is one of less average involvement. Father involvement, in turn, predicts healthier behavior from their children, such as reduced rates of smoking.[11] Many complex factors are shown to affect the probability of paternal involvement, including the degree of parental conflict, quality of past family relationships, and whether the father has ever been incarcerated.[12]

Another complex finding is that we observe a strong negative relationship between rates of religious membership and Black longevity, meaning Black people living in geographies with people who are more religious have lower life expectancies. This is somewhat puzzling, because people who are more religious are usually found to have better self-reported health (however, they are also more likely to be obese).[13] It is possible that areas with higher rates of religious participation tend to have other characteristics that are harmful to health (e.g., worse crime, less access to quality food, pollution). Also, the faithful may experience higher levels of suffering in ways that are not readily captured by income or education levels; people may seek religion when the rest of society devalues them.

An alternative explanation that links many of these findings is that health knowledge and access to information can have important effects on health. People with higher levels of education, numeracy, and literacy are found to exhibit both higher levels of health knowledge and engage in healthier behaviors. Having access to diverse social networkswhich we find predicts better healthmay also increase health knowledge by providing greater access to what works.

Regardless of the causal pathways, the 13 variables identified in our analysis explain roughly half of the variation between counties with respect to Black life expectancy. If a low-performing county were to become a high-performing county, predicted life expectancy would increase by an additional 14 years for the average Black resident.

Overall, this analysis will raise questions that we cannot confidently answer about the fundamental drivers of community health and well-being. We hope to refine and expand our analysis in updated versions of the Index. For now, we hope this research can encourage evidence-based analysis and policy discussions concerning the health of Black people and point toward collective action that help more communities thrive, regardless of their racial composition.

The authors thank Makada Henry-Nickie, Zinzi Bailey, Sheri Johnson, Christine Muganda, Keith Gennuso, and Regina Seo for comments and suggestions on previous versions of this report.

Appendix Table 1. The top 20 U.S. metropolitan areas with highest Black Progress Index score, actual life expectancy, and life years unexplained by model

[1] Measurement error, especially for smaller geographic areas, also causes a divergence between modeled life expectancy and observed life expectancy, and so a higher-than-predicted life expectancy does not necessarily mean that the area has some unmeasured positive effect on health.

[2] Bailey, Michael, Rachel Cao, Theresa Kuchler, Johannes Stroebel, and Arlene Wong. Social connectedness: Measurement, determinants, and effects.Journal of Economic Perspectives32, no. 3 (2018): 259-80.

[3] We find that air pollution is only weakly correlated with population density (r=0.09), but population density is very strongly correlated with the intensity of land use and negatively correlated with tree cover. For these reasons, we group population density under environmental conditions, but we do not claim that low-population-density areas have cleaner air or waterjust that they are exposed to more natural environments, including trees, depending on the climate.

[4] We considered other variables that may predict either safety or high levels of discrimination, such as the number of police officers per capita, deaths from police encounters per capita, hate crimes per capita, and anti-Black hate crimes per capita. None of these variables were statistically significant in predicting Black life expectancy in the presence of our other 13 variables, so they were not included in the final model.

[5] U.S. Arias E, Xu JQ. United States life tables, 2019. National Vital Statistics Reports; vol 70 no 19. Hyattsville, MD: National Center for Health Statistics. 2022. DOI: https://dx.doi.org/10.15620/cdc:113096

[6] We studied the cause of deathas recorded on death certificatesby age and race to calculate which causes account for the largest losses in potential life in 2020 (and thus contribute the most downward drag on longevity) for Black and white Americans. Deaths at early ages count proportionately more than deaths at older ages, because the death implies a larger loss of potential life when it happens early in life. We use age 100 as the reference age, because it is the oldest observable age in the CDC records. Thus, death at birth suggests a loss of 100 years, while death at 99 suggests a loss of one year. The Underlying Cause of Death data are produced by the Mortality Statistics Branch, Division of Vital Statistics, National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention (CDC), United States Department of Health and Human Services (US DHHS).

[7] Singh, Gopal K., and Barry A. Miller. Health, life expectancy, and mortality patterns among immigrant populations in the United States. Canadian journal of public health 95, no. 3 (2004): I14-I21.

[8] Dupre, Matthew E., Danan Gu, and James W. Vaupel. Survival differences among native-born and foreign-born older adults in the United States. PLoS One 7, no. 5 (2012): e37177.

[9] Cutler, David M., and Adriana Lleras-Muney. Understanding differences in health behaviors by education. Journal of health economics 29, no. 1 (2010): 1-28.

[10] Jones J, Mosher WD. Fathers involvement with their children: United States, 20062010.

National health statistics reports; no 71. Hyattsville, MD: National Center for Health Statistics. 2013.

[11] Menning, Chadwick L. Nonresident Fathers Involvement and Adolescents Smoking. Journal of Health and Social Behavior 47, no. 1 (March 2006): 3246. https://doi.org/10.1177/002214650604700103; Amato, P.R., and Gilbreth, J.G. Nonresident fathers and childrens well-being: A meta-analysis. Journal of Marriage and the Family (1999) 61:55773; Steinberg L. We know some things: Parentadolescent relationships in retrospect and prospect. Journal of Research on Adolescence. 2001;11:119.

[12] Perry, Armon R., and Mikia Bright. African American fathers and incarceration: Paternal involvement and child outcomes.Social work in public health27, no. 1-2 (2012): 187-203; Coley, Rebekah Levine, and Daphne C. Hernandez. Predictors of paternal involvement for resident and nonresident low-income fathers.Developmental psychology42, no. 6 (2006): 1041.

[13] Nam, Sanggon. The effects of religious attendance and obesity on health by race/ethnicity. Osong Public Health and Research Perspectives 4, no. 2 (2013): 81-88; Gillum, R. Frank. Frequency of attendance at religious services, overweight, and obesity in American women and men: the Third National Health and Nutrition Examination Survey. Annals of epidemiology 16, no. 9 (2006): 655-660.

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The Black Progress Index: Examining the social factors that influence Black well-being - Brookings Institution

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Scream is and will always be that slasher franchise. From its earliest conception by writer Kevin Williamson and director Wes Craven, it undoubtedly redefined the horror genre in the late 90s, eventually leading to the powerful cinematic nostalgia wave more than two decades later. However, soon enough, it will receive its monumental sixth entry to further cement itself as a totally timeless horror title.

When discussing his new slasher film recently, the topic (obviously) led to his work on Scream; Williamson was asked if he always thought it could go on for so long. Turns out, the versatile writer wasn't always so confident. The Scream 6 creative tells Collider, "Now [I do think it can]. I've been proven wrong repeatedly. Since this last one was such a pleasure I also think one of the wonderful things about Scream is that there's a different killer in every film. There's [Jason Voorhees, Michael Myers, or Freddy Krueger], they don't go away. And Ghostface changes with every movie, so we have an opportunity to change the motive, change the story, and we can always twist and turn it since it [the original Scream] was always meant to be a game-changer. "

The renowned Scream scribe then adds, "And I think this new team is awesome. They're absolutely amazing human beings. They're talented, and it's just been a pleasure to be a part of this new regime." When the topic naturally shifted to its brand new New York City setting for the next installment of Scream, Williamson was jokingly asked about the chance of a Ghostface Takes Manhattan reference to mirror the Friday the 13th-like switch-up, which actually led to the OG Scream mastermind to admit, "I think there's a joke in there."

Scream 6 will be released exclusively in theaters on March 31, 2023, starring several returning scream queens such as Melissa Barrera, Jenna Ortega, Hayden Panettiere, Courtney Cox, and Jasmin Savoy Brown, along with plenty of new blood for Ghostface to spill.

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Kevin Williamson on Scream 6 and Franchise Longevity - Bleeding Cool News