Our economy deteriorating pages– a collapsed economy already, for unequal communities

In this series on “Our economy deteriorating,” we’ve been focusing on the factors that can be leading up to “economic collapse” as is being ever-more frequently discussed in the alternative social science and economics literature.

People often ask, “What would that collapse look like? What would its characteristics be?” The further we delve into this question, the more it looks like a matter of how people who are in the middle range of the inequality spectrum would expect a collapse to look like, from their vantage point. However, from the perspective of people trapped at the very bottom ranges of the inequality spectrum or pyramid, it seems like a “privileged question.” Conditions at the bottom of inequality in the peak inequality economy/society look like those of an economy/society which is already in the midst of collapse, or has already collapsed.

That’s what this blog post will get at. Any updates and revisions will appear at bottom of the page.

Is Racism a Fundamental Cause of Inequalities in Health?

Jo C. Phelan and Bruce G. Link
Annual Review of Sociology, Vol. 41 (2015)

Abstract
We previously proposed that socioeconomic status (SES) is a fundamental cause of health inequalities and, as such, that SES inequalities in health persist over time despite radical changes in the diseases, risks, and interventions that happen to produce them at any given time. Like SES, race in the United States has an enduring connection to health and mortality. Our goals here are to evaluate whether this connection endures because systemic racism is a fundamental cause of health inequalities and, in doing so, to review a wide range of empirical data regarding racial differences in health outcomes, health risks, and health-enhancing resources such as money, knowledge, power, prestige, freedom, and beneficial social connections.

We conclude that racial inequalities in health endure primarily because racism is a fundamental cause of racial differences in SES and because SES is a fundamental cause of health inequalities. In addition to these powerful connections, however, there is evidence that racism, largely via inequalities in power, prestige, freedom, neighborhood context, and health care, also has a fundamental association with health independent of SES.


—————————————

In searching the scholarly, peer-reviewed literature, we looked up the phrase “life expectancy by U.S. zip code.” This is where the real cost of wealth and income inequality clearly shows, and the cost is in terms of years of life, as well as a person’s general health conditions during their shorter life than the people higher up the wealth scale. Someone suggested this story to me, and I found this the best place to start in this brief review of the literature on inequality of mortality in the United States.

Why Americans Die So Much

U.S. life spans, which have fallen behind those in Europe, are telling us
something important about American society.
by Derek Thompson
The Atlantic, Sept. 12,2021

I’m talking about the past 30 years. Before the 1990s, average life expectancy in the U.S. was not much different than it was in Germany, the United Kingdom, or France. But since the 1990s, American life spans started falling significantly behind those in similarly wealthy European countries.

According to a new working paper released by the National Bureau of Economic Research, Americans now die earlier than their European counterparts, no matter what age you’re looking at. Compared with Europeans, American babies are more likely to die before they turn 5, American teens are more likely to die before they turn 20, and American adults are more likely to die before they turn 65. At every age, living in the United States carries a higher risk of mortality. This is America’s unsung death penalty, and it adds up. Average life expectancy surged above 80 years old in just about every Western European country in the 2010s, including Portugal, Spain, France, Italy, Germany, the U.K., Denmark, and Switzerland. In the U.S., by contrast, the average life span has never exceeded 79—and now it’s just taken a historic tumble.

…“Europe has better life outcomes than the United States across the board, for white and Black people, in high-poverty areas and low-poverty areas,” Hannes Schwandt, a Northwestern University professor who co-wrote the paper, told me. “It’s important that we collect this data, so that people can ask the right questions, but the data alone does not tell us what the cause of this longevity gap is.”

…Europe’s mortality rates are shockingly similar between rich and poor communities. Residents of the poorest parts of France live about as long as people in the rich areas around Paris do. “Health improvements among infants, children, and youth have been disseminated within European countries in a way that includes even the poorest areas,” the paper’s authors write.

.But in the U.S., which has the highest poverty and inequality of just about any country in the Organization for Economic Cooperation and Development, where you live is much more likely to determine when you’ll die. Infants in the U.S. are considerably more likely to die in the poorest counties than in the richest counties, and this is true for both Black and white babies. Black teenagers in the poorest U.S. areas are roughly twice as likely to die before they turn 20, compared with those in the richest U.S. counties. In Europe, by contrast, the mortality rate for teenagers in the richest and poorest areas is exactly the same—12 deaths per 100,000. In America, the problem is not just that poverty is higher; it’s that the effect of poverty on longevity is greater too.

Concludes Derek Thompson:

For decades, U.S. politicians on the right have resisted calls for income redistribution and universal insurance under the theory that inequality was a fair price to pay for freedom. But now we know that the price of inequality is paid in early death—for Americans of all races, ages, and income levels. With or without a pandemic, when it comes to keeping Americans alive, we really are all in this together.


In Thompson’s Atlantic piece he references this study in National Bureau of Economic Research:

Archived here in he blog files–and downloadable to you–The NBER paper notes improvement in the gap between black and white child deaths over the decades from 1990 through 2018. Nonetheless, there were still two black children dying for every white child, in 2018.

The NBER study is archived here on the blog files, and should be downloadable to you here:

When we zoom in to the Zip Code level, geographically mapping out inequality of differences in life expectancy, we can focus more on inequality as Professor Dorling of Oxford University has done in the United Kingdom, contributing to his book “Peak Inequality: “Britain’s Ticking Time Bomb.”

For example, let’s look at this study —

Life Expectancy at Birth in Milwaukee County: A Zip Code-Level Analysis

J Patient Cent Res Rev. 2017 Fall; 4(4): 213–220.
Published online 2017 Nov 6. doi: 10.17294/2330-0698.1576

By Erica S. LeCounte, MPH and Geoffrey R. Swain, MD, MPH


Methods

To calculate life expectancy, death count data and population estimates were entered into an abridged life table using the Chiang methodology. Data were linked with measures from the American Community Survey to examine the relationship between life expectancy and zip code characteristics.

Results

Life expectancy varies greatly across zip codes in Milwaukee County. Overall, there was a 12-year difference in the life expectancy of children born into zip codes with the lowest and highest life expectancy: 53206 (71.3 years) and 53217 (83.2 years). There was a strong positive correlation between life expectancy and median household income (r=0.784, P<0.0001), educational attainment of a bachelor’s degree or higher (r=0.741, P<0.0001) and the socioeconomic index combining education and income (r=0.819, P<0.0001).

Conclusions

Disparities in life expectancy within Milwaukee County are stark and correlate with differences in social and economic factors. To improve health outcomes such as life expectancy, health care practitioners and health care systems must become more involved in activities at the social and policy levels to improve social and economic conditions that would allow their patients to live healthier and longer lives.

1. Kochanek KD, Murphy SL, Xu J, Tejada-Vera B. Deaths: final data for 2014. Natl Vital Stat Rep. 2016;65(4):1–122. [PubMed] [Google Scholar]
2. Wisconsin Department of Health Services, Division of Public Health, Office of Health Informatics. Wisconsin Life Expectancy Report, 2010–2014 (P-01551) [Accessed August 30, 2016]. https://www.dhs.wisconsin.gov/publications/p01551.pdf.
3. Institute for Health Metrics and Evaluation. County profile: Milwaukee County, Wisconsin. [Accessed June 28, 2017]. Published 2016. http://www.healthdata.org/sites/default/files/files/county_profiles/US/2015/County_Report_Milwaukee_County_Wisconsin.pdf.
4. Virginia Commonwealth University Center on Society and Health. Mapping life expectancy. [Accessed May 30, 2017]. Published September 26, 2016. http://www.societyhealth.vcu.edu/work/the-projects/mapping-life-expectancy.html.
5. Jackson County Health Department, Division of Community Health Promotion. Place matters: life expectancy in Eastern Jackson County. [Accessed May 30, 2017]. Published January 2017. http://jacohd.org/files/place-matters/place-matters-2017.pdf.
6. University of Wisconsin Population Health Institute. 2017 County Health Rankings key findings report. [Accessed May 30, 2017]. Published 2017. http://www.countyhealthrankings.org/reports/2017-county-health-rankings-key-findings-report.
7. Hood CM, Gennuso KP, Swain GR, Catlin BB. County health rankings: relationships between determinant factors and health outcomes. Am J Prev Med. 2016;50:129–35. doi: 10.1016/j.amepre.2015.08.024. [PubMed] [CrossRef] [Google Scholar]
8. Chiang CL. Introduction to Stochastic Processes in Biostatistics. New York, NY: John Wiley & Sons; 1968. The Life Table and its construction; pp. 189–214. [Google Scholar]
9. Vila PM, Swain GR, Baumgardner DJ, Halsmer SE, Remington PL, Cisler RA. Health disparities in Milwaukee by socioeconomic status. WMJ. 2007;106:366–72. [PubMed] [Google Scholar]
10. U.S. Census Bureau, American Fact Finder. 2010–2014 American Community Survey. [Accessed June 19, 2017]. https://factfinder.census.gov.
11. Ngui E, Michalski K, LeCounte E, Mohr A. 2017 City of Milwaukee Fetal Infant Mortality Review (FIMR) Report: Status Report on 2012–2015 Stillbirths and Infant Deaths. Milwaukee: WI: City of Milwaukee Health Department and Zilber School of Public Health; Apr, 2017. [Google Scholar]
12. Greer DM, Baumgardner DJ, Bridgewater FD, et al. Milwaukee Health Report 2013: Health Disparities by Socioeconomic Status. Milwaukee, WI: Center for Urban Population Health; 2013. [Google Scholar]
13. Burd-Sharps S, Lewis K. A Portrait of California: California Human Development Report 2011. Brooklyn, NY: American Human Development Project of the Social Science Research Council; 2011. [Google Scholar]
14. Swain GR, Grande KM, Hood CM, Inzeo PT. Health care professionals: opportunities to address social determinants of health. WMJ. 2014;113:218–22. [PubMed] [Google Scholar]
15. Catlin BB, Bergum AH, Russ J. What Works? Policies and Programs to Improve Wisconsin’s Health. Madison, WI: University of Wisconsin Population Health Institute; Sep, 2012. [Google Scholar]
16. Human Impact Partners. Completed projects. [Accessed June 29, 2017]. http://www.humanimpact.org/projects/past-projects/
17. Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood) 2002;21:60–76. doi: 10.1377/hlthaff.21.2.60. [PubMed] [CrossRef] [Google Scholar]
18. Heiman HJ, Artiga S. [Accessed June 29, 2017];Beyond health care: the role of social determinants in promoting health and health equity. Published November 2015. http://files.kff.org/attachment/issue-brief-beyond-health-care. [Google Scholar]
19. Council on Community Pediatrics. Poverty and child health in the United States. Pediatrics. 2016;137(4):e20160339. doi: 10.1542/peds.2016-0339. [PubMed] [CrossRef] [Google Scholar]

The entire Google Scholar search by the string “Life expectancy varies by U.S. Zip code” can be found here, approx. 15,000 entries from 2017.

Given what we have read so far, we may ask ourselves, “has the response to the Covid-19 pandemic resulted in a big and wide national reform movement to overcome the peak inequality impacting on the standard of living of black, indigenous, and people of color communities as measured quantitatively and qualitatively in the USA?”

This paper published by National Center for Biotechnology Information-National Library of Medicine located on the National Institutes of Health website provides an answer to that question.

Online at

National Disparities in COVID-19 Outcomes between Black and White Americans

Michael Poulson, Alaina Geary, Chandler Annesi, Lisa Allee, Kelly Kenzik, Sabrina Sanchez, Jennifer Tseng, Tracey Dechert

National Center for Biotechnology Information
National Library of Medicine
National Institutes of Health website

Here is what these authors found:

Abstract

Background: There is very limited comprehensive information on disparate outcomes of black and white patients with COVID-19 infection. Reports from cities and states have suggested a discordant impact on black Americans, but no nationwide study has yet been performed. We sought to understand the differential outcomes for black and white Americans infected with COVID-19.

Methods: We obtained case-level data from the Centers for Disease Control and Prevention on 76,442 white and 48,338 non-Hispanic Black patients diagnosed with COVID-19, ages 0 to >80+, outlining information on hospitalization, ICU admission, ventilation, and death outcomes. Multivariate Poisson regressions were used to estimate the association of race, treating white as the reference group, controlling for sex, age group, and the presence of comorbidities.

Results: Black patients were generally younger than white, were more often female, and had larger numbers of comorbidities. Compared to white patients with COVID-19, black patients had 1.4 times the risk of hospitalization (RR 1.42, p < 0.001), and almost twice the risk of requiring ICU care (RR 1.68, p < 0.001) or ventilatory support (RR 1.81, p < 0.001) after adjusting for covariates. Black patients saw a 1.36 times increased risk of death (RR 1.36, p < 0.001) compared to white. Disparities between black and white outcomes increased with advanced age.

Conclusion: Despite the initial descriptions of COVID-19 being a disease that affects all individuals, regardless of station, our data demonstrate the differential racial effects in the United States. This current pandemic reinforces the need to assess the unequal effects of crises on disadvantaged populations to promote population health.

————————————————–

This particular posting on the blog has been drawing together two meta-narratives: The deterioration of the economy of our United States of America, coupled with the “peak inequality” of wealth, income, and the inequality of political-personal power derivative from that peak wealth inequality. We should also recognize that mapping “unequal communities” for example by County or more micro, by zip code data, will reveal that many of the unequal communities now living in a collapsed economy are also majority-white-person communities. This is the uncomfortable truth which national politicians trafficking in white supremacist narratives would prefer not to see the light of day.

met·a·nar·ra·tive /ˈmedəˌnerədiv/
noun

  • 2. an overarching account or interpretation of events and circumstances that provides a pattern or structure for people’s beliefs and gives meaning to their experiences:

Any readers of the blog who would be interested in contributing future posts on topics such as these, or to take part in a podcast series called “Abolish Inequality Podcast” may contact us here:
greenpeoplesmedia@gmail.com

Nouriel Roubini – Ten Deadly Drivers of the Greater Depression of the 2020s – Update

“and I pointed out there were ten deadly drivers of this disruption and economic deficiencies.

This started after the Global Financial Crisis, but they are being exacerbated by this Coronavirus crisis.

1. Things like tax deficits and default.
2. Poor demographics is going to be a big liability.
3. Or initially deflation, followed by debasement of currencies as we monetize the fiscal deficits; we’re going to end up, eventually with inflation.
4. We have features of disruption with A.I. and automation.
5. And then, rising inequality.
6. And then you have de-globalization, as there is a backlash against trade, immigration and open markets.
7, And then you have a democracy backlash.
8. And then from there you go to this duopolistic rivalry between the U.S. and China,
9. and the digital rivalry between U.S. and China as well.
10. And you finish with deadly, manmade disasters like pandemics and climate change–they’re not natural disasters, but as we know are manmade.

You combine these ten forces–and they’re all very disruptive–and you might have, eventually, a greater depression. But this is not the story for this year or next, but for the middle of the decade.”

Update, end September, 2021
In the ongoing series of posts on “Our economy deteriorating,” we would like to include additional drivers of the Greater Recession–
11. Secular stagnation of wages in our economic system, a risk factor for collapse and
12. The world oil shocks / world energy shocks scenarios about to roll out at mid-decade, from mid-2025 onward. These scenarios will make it difficult-to-impossible to re-start the “growth engine” which for 120 years has been fueled by growth in fossil fuels consumption.
A Dozen Deadly Drivers of economic crises. No community, no county, no state will avoid these crises. We had all better begin to prepare for a wholly different world ahead.

Who is Nouriel Roubini?

Nouriel Roubini (born March 29, 1958) is an American economist He teaches at New York University’s Stern School of Business and is chairman of Roubini Macro Associates LLC, an economic consultancy firm.

The child of Iranian Jews, he was born in Turkey and grew up in Italy. After receiving a BA in political economics at Bocconi University, Milan and a doctorate in Intenational Economics at Harvard, he became an academic at Yale and a visiting researcher/advisor at the International Monetary Fund (IMF), the Federal Reserve, World Bank, and Bank of Israel. Much of his early research focused on emerging markets. During the administration of President Bill Clinton, he was a senior economist for the Council of Economic Advisers, later moving to the United States Treasury Department as a senior adviser to Timothy Geithner, who was Treasury Secretary under Barack Obama.



UW Divestment Coalition Banner Drop at UWSP

On September 24 2021, the UW Divestment Coalition had another “banner drop”at a busy crossing point for students on the Univesity of Wisconsin-Stevens Point campus.

The first video is an interview with Molly McGuire, the Vice-President of 350-Stevens Point, a local chapter of the large national movement 350-Org founded by Bill McKibben. The Stevens Point chapter’s officers are all students at UW-Stevens Point, which is unique among environmental groups in this state.

UW Divestment Coalition:
https://www.uwdivestment.com/



Next is a brief interview with Lucy, Action Coordinator of the UW Divestment Coalition at University of Wisconsin-Stevens Point. The musical soundtrack was not intentional, but part of the background sound outside the athletic building where the students were coming and going.

350 Stevens Point

President: Gabrielle Arnold

Vice President: Molly McGuire

Treasurer

Public Relations: Katherine McClure

Secretary: Cailey Wolf

Check us out online!

SPIN ~ https://uwsp.collegiatelink.net/organization/350

FB ~ www.facebook.com/350stevenspoint

Insta ~ @350stevenspoint

WordPress ~ https://350sp.wordpress.com/