Flowing Data has a new data visualization of smokers in 1994 and 2014 by gender, education, income, and race & origin.
Two decades out from the 1995 law in California, along with the known impact of smoking on one’s health, you’d think smoking rates would be way down. And you’d be right for many demographic groups, but for some, smoking is still the same as it ever was.
[The charts] show estimated percentage of adult smokers among different groups, for 1994 and 2014. Estimates are based on survey data from the Behavioral Risk Factor Surveillance System.
Since 2014, The ACA Implementation Network (of the Rockefeller Institute of SUNY, the Brookings Institution and the Fels Institute of Government of the University of Pennsylvania) has been producing state-wide reports to try to answer the following questions:
- Who governs state health reform initiatives and activities?
- What new federal-state and inter-agency relationships have developed under the ACA?
- And how have states put the principal coverage-related policies into operation, and with what effects?
The state reports are available by clicking on the map at the Network’s website. There are also two region-wide reports: the Western Overview Report and the Southern Overview Report.
H/T Data Detectives
The NIH Office of Behavioral and Social Sciences blog highlighted research by Ann Marie White and Melanie Funchess on the use of “Twitter data to prevent violence and suicide through community-based helping networks.”
Their recent BSSR talk, “To tweet or not to tweet: Community-based participatory research approaches to advance wellness and violence prevention via social media,” highlighted their progress in developing community-based helping networks that take advantage of social media tools to improve public health in their neighborhoods.
The World Bank has a new interactive chart showing how the leading causes of death are changing worldwide:
From The DataBlog:
Worldwide, the leading causes of death are changing, and they vary between rich and poor countries. In low-income countries, deaths from communicable diseases such as malaria and HIV/AIDS have fallen, while deaths from non-communicable diseases such as stroke and diabetes are on the rise.
Julie Mack of MLive.com put together mortality statistics from the Michigan Department of Health and Human Services and found some interesting trends.
A century ago, in 1914, 13 percent of people died from heart disease and 6 percent from cancer. That’s an era when contagious disease and infection killed many people at a much younger age.
In 1964, a half-century ago, after the introduction of antibiotics, heart disease and cancer together accounted for 55 percent of Michigan deaths.
In recent years, heart disease has been declining as a cause of death, while cancer has been on the increase.
Remember: Causes of death are a zero-sum situation. Since everybody dies, if one cause goes down, another must increase.
See also: Michigan’s top 10 causes of death.
Richard Hodes, director of the National Institute on Aging, wrote in the Inside NIA bog about their updated version of the NIA’s Strategic Directions, Aging Well in the 21st Century.
NIA’s previous strategic approach was published in 2007. Since then, we have made a number of important revisions. Most critically, we have organized our approach into three “functional” areas:
- Understanding the Dynamics of the Aging Process
- Improving the Health, Well-Being, and Independence of Adults as they Age
- Supporting the Research Enterprise
Read the full post.
The CDC released a new Fact Sheet showing the lifetime risk of HIV diagnosis in the United States.
From the press release:
CDC researchers used diagnoses and death rates from 2009-2013 to project the lifetime risk of HIV diagnosis in the United States by sex, race and ethnicity, state, and HIV risk group, assuming diagnoses rates remain constant. Overall, the lifetime risk of HIV diagnosis in the U.S. is now 1 in 99, an improvement from a previous analysis using 2004-2005 data that reported overall risk at 1 in 78.
Nathan Yau of Flowing Data has been doing some interesting (and beautiful) visualizations of when and how people die. First was Years You Have Left to Live, Probably. Next was Causes of Death. And today he posted How You Will Die.
Philip Cohen, writing for the Family Inequality blog, has some concerns about the Case and Deaton paper showing that the mortality rate for middle-aged white men is rising: “My concern is that changes in the age and sex composition of the population studied could account for a non-trivial amount of the trends they report.”