Health and Medical News and Resources

General interest items edited by Janice Flahiff

[Report] DEATH RATES FROM MAJOR CAUSES IN THE UNITED STATES, 2010-2011

From the Insurance Information Institute

(another table on accident risks at the above link)

HEALTH RISKS

Heart disease is the leading cause of death in the U.S., accounting for nearly 600,000 fatalities in 2010, according to the Centers for Disease Control. Influenza and pneumonia ranked ninth in 2010, accounting for some 50,000 fatalities. However, pandemic influenza viruses have the potential to be far more deadly. An estimated 675,000 Americans died during the 1918 Spanish influenza pandemic, the deadliest and most infectious known influenza strain to date.

DEATH RATES FROM MAJOR CAUSES IN THE UNITED STATES, 2010-2011

Age-adjusted death rate (1)
Cause of death Number of deaths, 2011 2010 2011 (2) Percent change
Heart disease 596,339 179.1 173.7 -3.0%
Malignant neoplasms (tumors) 575,313 172.8 168.6 -2.4
Chronic lower respiratory diseases 143,382 42.2 42.7 1.2
Cerebrovascular diseases (stroke) 128,931 39.1 37.9 -3.1
Accidents (unintentional injuries) 122,777 38.0 38.0 (3)
Alzheimer’s disease 84,691 25.1 24.6 -2.0
Diabetes 73,282 20.8 21.5 3.4
Influenza and pneunonia 53,667 15.1 15.7 4.0
Kidney disease 45,731 15.3 13.4 -12.4
Intentional self-harm (suicide) 38,285 12.1 12.0 -0.8
Septicemia 35,539 10.6 10.5 -0.9
Chronic liver disease and cirrhosis 33,539 9.4 9.7 3.2
Hypertension (4) 27,477 8.0 8.0 (3)
Parkinson’s disease 23,107 6.8 7.0 2.9
Pneumonitis due to solids and liquids 18,090 5.1 5.3 3.9
All other causes 512,723 NA NA NA
Total deaths 2,512,873 747.0 740.6 -0.9%

(1) Per 100,000 population; factors out differences based on age.
(2) Preliminary.
(3) Less than 0.1 percent.
(4) Essential (primary) hypertension and hypertensive renal disease.

NA=Not applicable.

Source: National Center for Health Statistics.

View Archived Tables

 

Additional Resource
Health Statistics Resources (jflahiff.wordpress.com)

 

February 19, 2015 Posted by | Health Statistics | , | Leave a comment

What Doctors Don’t Know & Journalists Don’t Convey About Screening May Harm Patients

From the 8 March 2012 blog item by Gary Schwitzerat at HeatlhNewsReview.org

A paper in the Annals of Internal Medicine this week asked (and partially answered): “Do Physicians Understand Cancer Screening Statistics?

The authors – familiar names like Woloshin, Schwartz, Gigerenzer – are from the Harding Center for Risk Literacy at the Max Planck Institute for Human Development in Berlin and from the Dartmouth Institute for Health Policy and Clinical Practice.

It’s a shame this paper isn’t freely, publicly available to all readers because it may help explain some of the foundation of the dilemma we face in this country about miscommunication about the tradeoffs involved in screening tests.

Reuters Health reported:

“…three-quarters of the more than 400 doctors surveyed believed better survival rates prove screening is a lifesaver although that’s not the case, researchers say.

And nearly half thought early detection translates into saving lives — another common misperception.

“This is really unfortunate because one of the things we always say is, ‘Discuss it with your doctor,’” said Dr. Otis Brawley, chief medical officer of the American Cancer Society. “This is evidence that your doctor doesn’t know.”…

Dr. Steven Woloshin, of Dartmouth Medical School in Hanover, New Hampshire, who worked on the new survey…told Reuters Health that death rates gleaned from clinical trials are the only reliable way to judge if a screening test is effective. But organizations that promote screening, such as the breast cancer charity Susan G. Komen for the Cure, tend to prefer survival rates, which sound more impressive…

 Dr. Virginia Moyer of Baylor, also chair of the US Preventive Services Task Force, wrote an accompanying editorial, “What We Don’t Know Can Hurt Our Patients: Physician Innumeracy and Overuse of Screening Tests.“  In it, she mentioned our work:

“Excellent work on how to effectively communicate statistical data to both patients and physicians has been done, but more is needed. Work of this sort is being supported by the Agency for Healthcare Research and Quality and such groups as the Foundation for Informed Medical Decision Making. To temper the unbridled enthusiasm of patients for screening tests, and especially for cancer screening, we need to reach beyond medicine to the public, which of course gets a substantial amount of medical information from the media. Educational efforts should focus not just on medical students and physicians but also on journalists. Several medical journals have taken the lead in making it easier for journalists to get the statistics right and to recognize the limitations of the studies they report. Watchdog groups, such as HealthNewsReview.org, help to monitor press reports and should be encouraged to add interpretation of screening statistics to the criteria they use to assess health news stories.”…

 

March 14, 2012 Posted by | health care | , , , , | Leave a comment

The future of death in America

From the report summary at the Max Planck Institute for Demographic Research

Abstract
Population mortality forecasts are widely used for allocating public health expenditures, setting research priorities, and evaluating the viability of public pensions, private pensions, and health care financing systems. Although we know a great deal about patterns in and causes of mortality, most forecasts are still based on simple linear extrapolations that ignore covariates and other prior information. We adapt a Bayesian hierarchical forecasting model capable of including more known health and demographic information than has previously been possible. This leads to the first age- and sex-specific forecasts of American mortality that simultaneously incorporate, in a formal statistical model, the effects of the recent rapid increase in obesity, the steady decline in tobacco consumption, and the well known patterns of smooth mortality age profiles and time trends. Formally including new information in forecasts can matter a great deal. For example, we estimate an increase in male life expectancy at birth from 76.2 years in 2010 to 79.9 years in 2030, which is 1.8 years greater than the U.S. Social Security Administration projection and 1.5 years more than U.S. Census projection. For females, we estimate more modest gains in life expectancy at birth over the next twenty years from 80.5 years to 81.9 years, which is virtually identical to the Social Security Administration projection and 2.0 years less than U.S. Census projections. We show that these patterns are also likely to greatly affect the aging American population structure. We offer an easy-to-use approach so that researchers can include other sources of information and potentially improve on our forecasts too.

Author’s affiliation
Samir Soneji
Dartmouth College, United States of America
Gary King
Harvard University, United States of America

December 8, 2011 Posted by | Public Health | , , , | Leave a comment

   

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