Archive for the 'Population Health & Health Disparities' Category

Vital Statistics: the Puerto Rico edition

When President Trump visited Puerto Rico after Hurricane Maria, he noted that only 16 people had died and compared that to the death toll after Hurricane Katrina:

“Sixteen people certified.” Trump said on October 3 during his visit to the island, repeating a figure confirmed by the territory’s governor. “Everybody watching can be very proud of what’s taken place in Puerto Rico.”

This was an improbably low number and immediately there were some posts suggesting that looking at vital statistics records could clarify this:

Everything that’s been reported about deaths in Puerto Rico is at odds with the official count
Eliza Barclay and Alexia Fernandez Campbell | Vox
October 11, 2017
According to this article, the method in use for the 16 certified deaths:

. . . “every death must be confirmed by the Institute of Forensic Science, which means either the bodies have to be brought to San Juan to do an autopsy or a medical examiner must be dispatched to the local municipality to verify the death”

Methodology suggested by John Mutter, Columbia University

. . . count all the deaths in the time since the event, and then compare that number to the average number of deaths in the same time period from previous years. Subtract the average number from the current number and that’s the death toll.

Rather than waiting for a year for Puerto Rican deaths to show up on the CDC website, investigators went to Puerto Rico to look at the vital registration system. Here’s a sampling.

Estimates of excess deaths in Puerto Rico following Hurricane Maria
Alexis Santo-Lozada and Jeffrey Howard | SocArXiv Papers
November 21, 2017

Nearly 1,000 More People Died in Puerto Rico after Hurricane Maria
Center for Investigative Journalism
December 7, 2017

Official Toll in Puerto Rico: 64. Actual Deaths May be 1,052
Frances Robles, Kenan Davis, Sheri Fink, and Sarah Almukhtar | New York Times
December 9, 2017
And, this one wins the prize for the best graphics. The first graph shows the excess deaths over previous years; the second is a table that shows causes of death – not just drownings and electrocutions, which are typical for hurricane events.

excess death graph

table showing causes of death

Opoid Use and Labor Force Participation

US Map Opoids and LFP

Image link: Large | Small

Alan Krueger has a paper in Brookings Papers on Economic Activity on opoid use and labor force participation and it got quite a bit of press coverage as well. And, luckily for us, the data are also available:

Where have all the workers gone? An inquiry into the decline of the U.S. labor force participation rate
Alan Kruger | Brooking Papers on Economic Activity
Fall 2017
This paper is part of the Fall 2017 edition of the Brookings Papers on Economic Activity, the leading conference series and journal in economics for timely, cutting-edge research about real-world policy issues.

Paper | Data | Slides [Krueger] | Slides [Katz, discussant] | Slides [Notowidigdo, discussant]

Additional Coverage
How the opioid epidemic has affected the U.S. labor force, county-by-county
Fred Dews | Brookings Now
September 7, 2017

The Opioid Crisis Is Taking a Toll on the American Labor Force
Eric Levitz | New York Magazine
Sep 7, 2017

The stunning prevalence of painkiller use among unemployed men
Danielle Paquette | WonkBlog: Washington Post
Sep 7, 2017

Drugs Are Why 1 in 5 Men Drop Out of the Labor Market
Sy Mukherjee | Fortune
Sep 7, 2017

One in Five Men Leave Workforce due to Opioid Epidemic, so Drugs – not Immigrants – are Stealing Jobs
John Haltiwanger | Newsweek
Sep 7, 2017

News: Certificate of Confidentiality

Rebecca Clark sent out some news via Twitter today:

Tweet


Here’s the official notice from NIH:

NOT-OD-17-109: Notice of Changes to NIH Policy for Issuing Certificates of Confidentiality

Missing Data

No not the ‘9’ code in data, but data that no longer exist.

The FiveThirtyEight blog has a nice post on data on drug use that no longer exists.

Data On Drug Use Is Disappearing Just When We Need It Most
Kathryn Casteel | FiveThirtyEight blog
June 29, 2017

The main source researchers use to determine patterns of drug use is the National Survey on Drug Use and Health and it doesn’t track very well with heroin mortality statistics. But, it is the best data researchers have:

Several other sources that researchers once relied on are no longer being updated or have become more difficult to access. The lack of data means researchers, policymakers and public health workers are facing the worst U.S. drug epidemic in a generation without essential information about the nature of the problem or its scale.

The rest of the post describes some data sources that no longer exist, which were useful indicators of heroin use:

Arrestee Drug Abuse Monitoring Program [ADAM].
Estimates of expenditures on heroin

Expenditures on illicit drug use are nicely summarized in this article:

Cocaine’s fall and marijuana’s rise: questions and insights based on new estimates of consumption and expenditures in US drug markets
Caulkins, J., B. Kilmer, P. Reuter, G. Midgette | Addiction
May 2015

And, not mentioned at all in the FiveThirtyEight post are patterns of drug usage from wastewater analysis – sewage epidemioloogy:

Real-Time Wasterwater Analysis Shows What Drugs are being Used Where
Douglas Main | Popular Science
June 11, 2014

Health ABC data available through NIA website

NIA’s Health, Aging and Body Composition (Health ABC) Study is now available on NIA’s website for qualified researchers.

The Health, Aging and Body Composition (Health ABC) Study began in 1997 and collected data for 17 years on a cohort of older black and white adults living in Memphis and Pittsburgh. Participants were aged 70-79 at baseline…

…[It] is an interdisciplinary study focused on risk factors for functional decline in healthy older people. With a particular focus on change in body composition with age, the study was designed to address differences in onset of functional limitation, disability, and longevity between older men and women, as well as between blacks and whites.

Read more on the Inside NIA blog.

Great Tweetstorm: Most important year in Economics?

This is from the blogger @undercoverhistorian. We had a previous post on the site she maintains. Below is an interesting set of almost 50 tweets – some illustrated – where she defends 1952 as the most important year.

twitter feed
Click here for tweetstorm

Health Care, Hepatitis C and Prisons

Anna Maria Barry-Jester has a piece in FiveThirtyEight examining the rate of hepatitis C & treatment in prisons by state.

The Federal Bureau of Prisons has guidelines for treating prisoners that include providing the new drugs. But the vast majority of U.S. prisoners are held in state facilities; about 1.4 million people are in state prisons, compared with about 191,000 in federal prisons.

Advancing research into Alzheimer’s disease

A new post by Richard Hodes on the Inside NIA blog discusses the increase in public interest and funding in recent years, which allowed the NIA to approve 26 concept proposals for funding opportunities.

We expect to have a record number of new FOAs coming out over the next few months. The FOAs that will result from these concept proposals involve every NIA division; in a number of cases, two or more divisions will be co-sponsoring an FOA. The list of concepts is available online. Please take a look and start to think about the kinds of projects or studies you might propose.

We anticipate releasing the first group of these FOAs in the next four to six weeks. Others will follow over the next two to three months. We’ll be writing about each group in this blog, as well as announcing them in other venues.

Read Preparing for a possible future: Advancing research into Alzheimer’s disease

Mapping the Spread of Obesity

Nathan Yau at Flowing Data has an interactive graphic showing the growth of obesity rates by state, year (since 1985) and gender.

Data Mining and Predictors of Physical Activity in Older Urban Adults

A post by Sunmoo Yoon in the NIH OBSSR blog looks at the potential of data mining to offer insights into predictors of physical activity in older urban adults:

Only two out of ten older adults meet the national guidelines for physical activity in the United States. Little is known about interrelationships of many socio-ecological factors to improve physical activity behavior among Hispanic older adults. As we move towards a precision medicine approach, we need innovative strategies to discover precisely tailored targets and accurate interventions. Data mining has the potential to offer such insights.