Tag Archives: health

What were the leading causes of death in 2020?

The CDC’s report, Provisional Mortality Data – United States 2020 (3/31/2021) provides the chart presented here.  COVID-19 was the third leading cause of death, although there were only deaths attributed to COVID-19 for nine months of the year. There is also this:

During January–December 2020, the estimated 2020 age-adjusted death rate increased for the first time since 2017, with an increase of 15.9% compared with 2019, from 715.2 to 828.7 deaths per 100,000 population. COVID-19 was the underlying or a contributing cause of 377,883 deaths (91.5 deaths per 100,000). COVID-19 death rates were highest among males, older adults, and AI/AN and Hispanic persons. The highest numbers of overall deaths and COVID-19 deaths occurred during April and December. COVID-19 was the third leading underlying cause of death in 2020, replacing suicide as one of the top 10 leading causes of death (6).

The findings in this report are subject to at least four limitations. First, data are provisional, and numbers and rates might change as additional information is received. Second, timeliness of death certificate submission can vary by jurisdiction. As a result, the national distribution of deaths might be affected by the distribution of deaths from jurisdictions reporting later, which might differ from those in the United States overall. Third, certain categories of race (i.e., AI/AN and Asian) and Hispanic ethnicity reported on death certificates might have been misclassified (7), possibly resulting in underestimates of death rates for some groups. Finally, the cause of death for certain persons might have been misclassified. Limited availability of testing for SARS-CoV-2, the virus that causes COVID-19, at the beginning of the COVID-19 pandemic might have resulted in an underestimation of COVID-19–associated deaths.

There is a table with data of total and covid deaths by age, sex, and race/ethnicity, as  well as another chart.

What is the connection between crime and lead?

Kevin Drum asks a good question in his post How Many Cops Does New York City Need?  First note that violent crime has been dropping since around 1990 (see his graph copied here for examples). In particular for NYC:

The per capita number of police officers increased by about 10 percent through 2000 and then declined by about 20 percent through 2018. That’s nearly flat over the entire period. Violent crime, by contrast, plummeted 60 percent from its peak in 1990 through 2000 and then declined another 40 percent through 2018. That’s a total decrease of nearly 80 percent between 1990 and 2018.

Violent  crime has decreased even though the per capita number of cops has been nearly flat. So, why did crime decrease? There is overwhelming evidence that removing lead emissions from cars is the main driver of crime decline. I strongly encourage you to read Drum’s 2018 summary of the evidence.

So, why doesn’t anyone talk about lead and crime?

The second problem is among activists on both left and right who have their own pet theories. On the left, we tend to blame poverty, institutional racism, poor schooling, lousy housing, and so forth. On the right, the favorite targets are the breakdown of the family, too few cops, too few prisons, drugs, the decline of religion, and so forth. There is very little convincing evidence for any of this, while lead poisoning explains everything. But if lead poisoning is the answer, then everyone has to give up their pet theories about what happened between 1960 and 2010. That’s a tough ask.

We forget that there was a lot of violent crime in the 1980s. It had an impact on society in many ways. But, we are past that and removing lead from the environment is a permanent fix to the violent crime wave of the past. This should allow us to think differently about societal needs for policing.

The Drum post has two other graphics. The Statistics Projects page has the relevant lead and crime data.


How should we measure COVID-19 deaths?

The CDC’s new webpage Excess Deaths Associated with COVID-19 provides one method to measure pandemic related deaths:

Estimates of excess deaths presented in this webpage were calculated using Farrington surveillance algorithms (1). For each jurisdiction, a model is used to generate a set of expected counts, and the upper bound of the 95% Confidence Intervals (95% CI) of these expected counts is used as a threshold to estimate excess deaths. Observed counts are compared to these upper bound estimates to determine whether a significant increase in deaths has occurred. Provisional counts are weighted to account for potential underreporting in the most recent weeks. However, data for the most recent week(s) are still likely to be incomplete. Only about 60% of deaths are reported within 10 days of the date of death, and there is considerable variation by jurisdiction.

The interactive graphics allows the user to choose a jurisdiction and different data types. The graph here is for the U.S. and weekly excess deaths. All data can be downloaded as a csv file.

Where do we buy our food?

How you answer the question of where do you buy your food probably says a lot about your socioeconomic status. The chart here is from the Business Insider article Here’s where Americans are buying their groceries by Hayley Peterson (6/21/17).  Note that CVS, Walgreens, Dollar Tree, and Dollar General each outsell Whole Foods, for example. Why does this matter? The recent Guardian article Fears grow over ‘food swamps’ as drugstores outsell major grocers by Gabrielle Cannon (6/4/19) provides context.

Shelf-stable options tend to be highly processed and high in fat, sodium and sugar. Where they are the easiest option available, communities experience higher rates of chronic illness, like diabetes, heart disease and cancer.

“Highly processed food makes you sick,” says William McCarthy, an adjunct professor of public health at UCLA. “CVS and other pharmacies make money selling highly processed, long shelf-life foods, because it is all convenient.” But, he says, his research has shown that it’s not just about having more healthy options.


In a 2016 study, researchers stocked corner stores in “food swamps” across East Los Angeles with affordable produce, hoping to test whether food retail interventions could be successful. They weren’t. While perceptions of the stores and community accessibility changed, patrons continued to purchase processed food instead of the fresh stuff.

Grocery sales data is available for 2018 (estimated) from the Winsight Grocery Business article WGB, Kantar Reveal ‘The Power 20’ Retailers by Meg major and Jon Springer (7/17/2018). They estimate CVS as fourth in grocery sales with Dollar General and Dollar Tree at 12 and 17, respectively. The Guardian article links to a couple of studies with statistical information suitable for a stats course.


What are the predictions for antimicrobial resistance?

The OECD has resources related to antimicrobial resistance (AMR). A summary can be read in the article Stopping antimicrobial resistance would cost just USD 2 per person a year (7/11/18), which included the chart copied here.  The article is rich with quantitative information.

While resistance proportions for eight high-priority antibiotic-bacterium combinations increased from 14% in 2005 to 17% in 2015 across OECD countries, there were pronounced differences between countries. The average resistance proportions in Turkey, Korea and Greece (about 35%) were seven times higher than in Iceland, Netherlands and Norway, the countries with the lowest proportions (about 5%).

Resistance is already high and projected to grow even more rapidly in low and middle-income countries. In Brazil, Indonesia and Russia, for example, between 40% and 60% of infections are already resistant, compared to an average of 17% in OECD countries. In these countries, growth of AMR rates is forecast to be 4 to 7 times higher than in OECD countries between now and 2050.

The full report is available: Stemming the Superbug Tide Just A Few Dollars More. Two other pages have graphs. The Nov 11 post under the same title, Stemming the Superbug Tide Just A Few Dollars More, includes a map and two sets of graph with AMR trends by countries.  On another page, Trends in AMR prevalence rates 2005-2030, users can select up to eight specific bacteria resistance rates, such as Penicillin-resistant S. Pneumoniae prevalence rates, along with any country to create interactive charts of present and projected rates.  The data does not appear to be accessible, but the first article contains contact information at the bottom that might help in getting the data in these reports.

Life Expectancy vs Income Per Person

With health care in the news, let’s take a look at the knowledge that can be gained by using Gapminder. For example, the graph here is life expectancy vs income per person for 2015, with the bubbles representing population size of the country. Can you guess the bubble for the U.S.? Go to the graph on Gapminder to find out.  As a bonus their is a play button so that the graph will scroll from 1800 to 2015. You will also find a number of tools to change the graph and create others. All the data used by the Gapminder graphs is located on their data page.