Tag Archives: death rate

Longevity, By the Book

Cognitive psychology, Health, Media,

Here’s good news for readers. Book reading, sometimes maligned as a sedentary behavior that may harm your health, actually increases your life expectancy. This  according to a study by Avni Bavishi and two colleagues from the Yale University School of Public Health. Since this is a correlational study, and correlation does not imply causation, it’s worth looking at their methods in some detail.

The data came from 3635 participants in the University of Michigan’s Health and Retirement Study, a nationally representative sample of adults over 50. They were interviewed every other year between 2001 and 2012, during which time 27.4% of them died. Participants were asked how many hours they spent during the past week reading books. They were asked the same question regarding periodicals (magazines and newspapers). The average time spent reading books was 3.92 hours a week; for periodicals, it was 6.10 hours. The correlation between book and periodical reading was modest (r = .23).

The authors predicted that the effect of book reading on life expectancy would be mediated by cognitive engagement; that is, reading books causes you to think about them, which in turn increases your longevity. Cognitive engagement was measured by performance on eight mental tasks, including immediate and delayed recall, backward counting and object naming.

In a correlational study such as this, it is important to control for alternative explanations that might cause both reading and longevity. Three variables predicted greater book reading in their sample. Women read more than men, people with more education read more, and so did higher income people. The statistical analysis held these three variables constant, plus an impressive list of others: age, race, visual acuity, marital status, job status, depression, self-rated health, and the presence of seven health problems (cancer, heart disease, diabetes, etc.). The analysis also controlled for cognitive engagement scores at the beginning of the study.

The results showed that book reading increased longevity, and that the more time you spend reading, the greater the effect. The effect of reading books was greater than that of reading magazines and newspapers. By the end of the study, 27% of the book readers had died, compared to 33% of non-readers. Comparing book readers and non-readers at the time at which 20% of the participants had died, the readers had a survival advantage of 23 months.

fig-1-survival-advantage-associated-with-book-reading-unadjusted-survival-curves-jpgAs predicted, the effect of book reading on longevity was mediated by cognitive engagement. (See this earlier post for an explanation of mediational analysis.) The researchers suggested two ways in which reading books increases cognitive engagement. First of all, book reading is deep reading, meaning that the greater length of books encourages readers to ask questions as they go along and to draw connections between various parts of the book. Secondly, book reading promotes empathy with the persons you are reading about, which might lead to greater social intelligence.

Of course, it’s impossible to rule out all possible alternative explanations for these results. I’m troubled by the lack of control for the participants’ social capital—the sum total of people’s involvement in community life-–which is known to be related to good health and life expectancy. However, the relationship between social capital and reading is unclear. You could argue that people who are involved in the community have less time to read. On the other hand, community involvement may encourage reading. People may read books in order to discuss them with other people, who in turn may suggest new books to read.

If these findings are valid, they raise several interesting questions. For example, would listening to audiobooks produce the same survival advantage? That is, is it the act of reading that is beneficial, or is it the content, regardless of how it is accessed? Of course, content must have some effect, since periodicals were less beneficial than books. Future researchers might want to look at the differences between fiction and non-fiction, or between genres or topics. Mysteries, for example, would seem to encourage deep reading.

As the authors note, the average American over 65 spends 4.4 hours per day watching television. In a 2012 study similar to this one, Peter Meunnig and his colleagues found that TV viewing reduced longevity. Specifically, each hour of daily viewing cost their participants about 1.2 years of life expectancy. The effect was mediated by greater unhappiness, reduced social capital and lower confidence in social institutions. If people could be persuaded to spend some of that 4.4 hours reading instead, they might be doing themselves a favor in more ways than one.

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Don’t Worry, Be Happy?

Bullshit

White Prejudice Affects Black Death Rates

Health, Prejudice and discrimination, ,

Dr. Jordan Leitner of the University of California at Berkeley and three colleagues have published a study of the relationship between White racial attitudes and the health outcomes of Black Americans. Here are some things we already know:

  • African-Americans have a higher death rate from cardiovascular diseases (e.g., heart attacks, strokes) than White Americans. (Other diseases as well, of course.)
  • The perception by Blacks (and others) that they are being discriminated against (e.g., being followed by store employees, being pulled over by the police for a minor offense) is associated with physiological stress responses known to cause circulatory problems, and with increased mortality. However, since these studies measure perceived rather than actual discrimination, a skeptic could argue that Blacks only imagined that Whites were biased against them.
  • African-Americans have higher death rates in locations where national surveys show that anti-Black attitudes are greater. But since these surveys include both Black and White respondents, it could be argued that the results were influenced by the attitudes of Black people who hate themselves.

Social psychologists distinguish between two types of prejudice. Implicit bias refers to automatic responses that are unintentional, and of which people may not be aware. Implicit bias was not related to any of the outcomed measured in this study. Explicit bias refers to responses that are deliberate and intentional. In this study, explicit bias was defined as the difference between how warmly (on a 10-point scale) participants said they felt toward White and Black Americans.

Leitner and his colleagues used a data base from Project Implicit consisting of the scores of about 1.4 million White Americans on the Implicit Association Test (IAT), a measure of implicit bias, collected between 2003 and 2013. When filling out the IAT, the participants indicated their race, age and gender, and completed the measure of explicit bias. The county in which their computer was located was determined from their Internet protocol address. Although it is large, this is not a representative sample of Americans, since the participants were younger than the average resident of their county. To correct this bias, the researchers weighted the responses of older participants more heavily. The results were the same with or without this correction.

In Study 1, racial bias was correlated with data from a 2012 telephone survey by the Centers for Disease Control (CDC), in which both race and county of residence were identified. Two questions were of interest. Access to affordable health care was measured by asking respondents whether they had ever, in the past year, needed to see a doctor but did not because of the cost. Coronary disease diagnosis was indicated by whether they reported being told by a health professional that they had a heart attack or heart disease.

In Study 2, racial bias was related to county-level statistics, also from the CDC, indicating the age-adjusted death rates from circulatory diseases of Blacks and Whites from 2003 through 2013. To control for alternative explanations, the data analyses of both studies statistically eliminated the effects of the following county-level characteristics: population, education, income, residential segregation, housing density and geographical mobility.

Below are scatterplots showing the outcomes of the two studies. Each dot represents a county and the lines indicate the statistical averages.

  1. Blacks overall reported less access to affordable medical care. More importantly, as explicit racial bias among the county’s Whites increased, Blacks had less access to affordable medical care. Explicit bias did not affect Whites’ access to medical care.
  2. However, explicit bias had no significant effect on coronary disease diagnosis among either Blacks or Whites.
  3. In the second study, they found that the higher the explicit racial bias among Whites, the more likely both Blacks and Whites were to die of circulatory diseases. However, this relationship was stronger for Blacks than it was for Whites. For example, among counties in which Whites were high in explicit racial bias, the difference between Blacks’ and Whites’ death rates from circulatory diseases was 62 per 100,000. Among counties low in explicit bias, the difference was 35 deaths per 100,000.

According to the authors, this is the first large-scale study to demonstrate that White prejudice increases the death rate due to coronary disease of African-Americans living in the same counties. However, racial bias did not affect Black death rates due to cancer. Thus, physiological stress due to discrimination and its effects on the cardiovascular system appears to be critical in producing this effect.

The results of Study 1 imply that these increased deaths were also due in part to Blacks’ reduced access to affordable medical care. The failure of prejudice to affect coronary disease diagnosis among Blacks could be related to their difficulties in obtaining health care. Diagnosis and treatment require doctor visits, but death does not.

The fact that explicit racial bias predicted Black outcomes but implicit bias did not suggests that these health outcomes were an result of conscious bias on the part of the White majorities in these counties. Failure to provide adequate health care for poor people and minorities is an outcome of social policy decisions made by politicians and by corporate executives such as the managements of hospitals and clinics. Although the present data were collected prior to the Affordable Care Act, it would not be surprising if many of these same counties were located in states that failed to take advantage of the federal government’s offer to expand Medicaid in 2014.

I suspect that White prejudice at the community level has many other effects on the lives of African-Americans in addition to limiting access to health care. Black-White wage inequality and criminal justice policies affecting Blacks would seem to be obvious topics for future research.

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Outrage

The Implicit Association Test: Racial Bias on Cruise Control

Old-Fashioned Racism

Don’t Worry, Be Happy?

Health, Social psychology, ,

One of the core beliefs of positive psychology, also known as the psychology of happiness, has been seriously challenged. A major reason for the popularity of positive psychology is their claim that happiness leads to improved health and greater longevity. Not so, according to a new study by a research team headed by Dr. Bette Liu of Oxford University published in the medical journal The Lancet.

The study shows the difficulty of drawing causal inferences from correlational data. The majority of previous studies of the happiness-health hypothesis are correlational. The researchers measured both the participants’ happiness and their health at the same time and found a positive relationahip. However, a correlation between A and B could mean that A causes B, B causes A, or both A and B are jointly caused by some third variable, C. In other words, the previous studies have at least two problems.

  1. Directionality. Rather than happiness causing good health, it could be that good health is the reason people are happy. Is happiness a cause of good health, or an effect?
  1. Third variables. There an infinite number of other variables which might be correlated with happiness and health and might be causing both. An obvious possibility is social class. Poverty could be making people unhappy and also making it difficult for them to lead healthy lives or obtain adequate health care.

The Liu data come from the Million Women Study conducted in the United Kingdom. Participants were recruited between 1996 and 2001 and were tested three years after their recruitment. At this baseline measurement session, they were then asked whether they suffered from a list of common health problems, and to rate their health as “excellent,” “good,” “fair” or “poor.” Then they were asked, “How often do you feel happy?” The alternatives were “most of the time,” “usually,” “sometimes,” and “rarely/never.” Measures were also taken of how often they felt stressed, relaxed, and in control.

Data were also collected for 13 demographic and lifestyle variables: age, region, area deprivation (a measure of the wealth of their census area), education, whether living with a partner, number of children, body mass index, exercise, smoking, alcohol consumption, hours of sleep, religiosity, and participation in other community groups. In 2012, it was determined whether each woman had died and, if so, the cause. The average duration of the study, from testing to outcome, was 9.6 years. Not all women completed the baseline measurements, and those who suffered from serious health problems at that time were eliminated, leaving a total of about 720,000 participants.

Participants were combined into three groups: happy most of the time, usually happy, and unhappy. About 4% of the women had died by 2012. Controlling only for age, the researchers found a strong relationship between happiness and all-cause mortality. This replicates previous studies. However, poor health at baseline was strongly related to unhappiness. When self-rated health was statistically controlled, the relationship between happiness and mortality was no longer statistically reliable. When all 13 demographic and lifestyle variables—some of which were significantly related to mortality—were controlled, the relationship almost completely disappeared. Happiness was also unrelated to heart disease mortality and cancer mortality once baseline health was controlled.

When they controlled for baseline health, the same results were obtained substituting the measures of feeling stressed, relaxed and in control for the happiness measure. These four analyses are illustrated by these graphs. Notice the almost flat lines hovering around RR = 1. A rate ratio (RR) of 1 indicates that a person in this group was no more or less likely to die than anyone else in the sample.

gr5_lrg

In summary, the results are consistent with the reverse causality hypothesis: Good health causes happiness, rather than the reverse. As one of the authors, Dr. Richard Peto, said, “The claim that [unhappiness] is an important cause of mortality is just nonsense. . . . Many still believe that stress or unhappiness can directly cause disease, but they are confusing cause and effect.”

Negative results are usually not considered a sufficient reason to reject a hypothesis, because many things can go wrong that can cause a study to fail even when the hypothesis is true. However, the Million Women Study must be taken seriously due to its large sample size and long duration. Certainly it would be better if the study had included men and citizens of other countries. However, there is no obvious theoretical reason to think that the happiness-health relationship holds only for men and not women, and previous studies of  the effect size for men and women are inconsistent.

Although the authors statistically controlled 13 demographic and lifestyle variables, it is impossible to control all possible confounding variables. With these negative results, a critic would have to argue that some third variable is masking the relationship between happiness and health. That is, there would have to be a third variable that is positively related to happiness but that increases mortality and therefore counteracts the expected positive effect of happiness on health.

A comment published along with the study criticized their simple, one-item measure of happiness. However, many previous studies have used the same or a similar measure. More importantly, when baseline health was not controlled, the authors replicated the results of previous studies, which suggests that their measure is adequate. Nevertheless, I anticipate that some positive psychologists will speak philosophically about some deeper meaning of happiness, insisting that whatever they mean by happiness is still a cause of good health, despite these negative results.

There are probably hundreds of thousands of professionals—not just clinical psychologists, but pop psychology practitioners from A (art therapists) to Z (well, yoga instructors)—who promise their clients they will be happier as a result of their treatment, and who implicitly or explicitly promise better health as an indirect result. They will either ignore this study or scrutinize it carefully for flaws. It should be fun to watch.

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On Obama’s Speech

On Obama’s Speech

Economics, Health, , ,

So far, we have no evidence that the killers were directed by a terrorist organization overseas or that they were part of a broader conspiracy here at home. But it is clear that the two of them had gone down the dark path of radicalization, embracing a perverted interpretation of Islam that calls for war against America and the West.

In Sunday night’s televised address, President Barack Obama claimed that the threat of terrorism “has evolved into a new phase”—that of home-grown terrorists inspired by ISIS, but not acting at the direction of the ISIS leadership. Although the U.S. military and law enforcement have grown more successful at preventing “complex and multi-faceted attacks like 9/11,” terrorists are turning the “less complicated acts of violence,” such as mass killings. However, when Obama spoke about the steps we are going to take to fight this new threat—more bombing of Syria and Iraq, tighter security, etc.—they turned out to be more of the same policies we have already implemented to fight the old form of terrorism. Maybe that’s why Obama describes desribed this home-grown terrorism—in what may be the most memorable line of the speech—as “a cancer that has no immediate cure.”

The future of Muslim terrorism in this country will depend not only on whether we abandon our seemingly endless war to control Middle Eastern energy resources, but also on social and economic conditions here at home. Home-grown Muslim terrorism has many of the same causes as non-Muslim domestic terrorism. Since 9/11, 48 people have been killed by right wing extremists and 28 by Muslim extremists. Our success in preventing both types of murder will depend on our being able to maintain the loyalty of working class Americans at a time of increasing inequality.

I’ve previously discussed Thomas Piketty’s claim that economic inequality is an important cause of Middle Eastern terrorism. Alvaredo and Piketty attempted to measure the extent of inequality in the Middle East, a task made more difficult by the lack of accurate data. They estimate that the top 10% controls over 60% of Middle East income, while the top 1% controls over 25%. Although the average income in the United States is much higher, income inequality in the U.S. is almost as high as in the Middle East. (In the U.S., the top 1% takes in 23% of the income.) A large body of evidence shows a positive relationship between income inequality and violence. For example, the homicide rate is higher in more unequal countries, and income inequality also predicts differences in the homicide rates of U.S. states. It now appears that our bleak economic conditions are starting to influence the overall death rate.

There has been a long-term decline in U.S. mortality rates, making our lives longer and better. However, Princeton economists Anne Case and Angus Deaton report that between 1999 and 2013, there was a reversal of this trend for non-Hispanic whites aged 45-54. While from 1978 to 1998, the mortality rate for this group declined by about 2% per year, since 1999, it has been increasing by about .5% per year. This translates into 96,000 more deaths than if the mortality rate were flat, and almost 500,000 more deaths than if it had continued its 2% per year decline. Described by the authors as a surprise, this startling increase in deaths has received little attention from the corporate media (although I suspect life insurance companies are on red alert). The closest recent parallel is the increase in deaths in Russia after the fall of the Soviet Union. As Joe Biden might say, “This is a big f***ing deal!”

The reversal is specific to this middle-aged whites. Mortality rates for blacks, Hispanics, and older whites continued to decline. The mortality rate for Hispanics aged 45-54 (262 per 100,000) is lower than that of middle-aged whites (262 v. 415 per 100,000) and declined by 1.8% over the 14 year period. The mortality rate for middle-aged blacks is higher (582 per 100,000), and declined at a rate of 2.6% per year. (To put this in perspective, middle-aged whites now die 71% as often as middle-aged blacks, compared to 56% as often 14 years ago.)

The increase in mortality among middle-aged people is also specific to this country. The graph below compares U.S. whites to the same age group among U.S. Hispanics and the residents of six other industrialized countries. (Both the authors of the study and the New York Times chose to include U.S. Hispanics in this table, but not U.S. blacks. If they had included blacks, of course, they would have needed a much larger graph.)

white-American-deaths

This is largely a story about social class. Since they didn’t have income data, the authors used education as a substitute. The change was most pronounced among those with a high school education or less. Mortality in this subgroup rose by 22% over the 14-year period, while it remained stable among those with some college and declined for those with a college degree.

The immediate cause seems to be an increase in self-destructive behavior. The change is explained almost exclusively by increases in three causes of death—suicide (up 78%), accidental drug and alcohol poisoning (up 400%), and cirrhosis and other chronic liver diseases caused by alcoholism (up 46%). These folks are committing either rapid or slow suicide.

There was also an increase in morbidity, or poor health, in this subgroup. The percentage reporting themselves in good health declined, and more people reported chronic pain, serious psychological distress, and difficulty in carrying out the activities of daily life, such as walking or socializing with friends. This is consistent with reports of increases in white, middle class drug overdoses caused by overuse of pain medication. (Ironically, the increase in opiate addiction among whites may lead to a more humane drug policy.) Self-reported alcohol consumption also increased. The increased mortality is not explained by obesity, since it occurred at about equal rates for obese and non-obese people.

ST_2015-12-09_middle-class-03

Case and Deaton attribute these changes to the decline in the standard of living and increasing economic insecurity among middle-aged whites. Deaton suggested in an interview that whites have “lost the narrative of their lives”—that is, they must face the reality that they are unlikely to have a financially secure retirement. A non-college graduate who was 50 in 2013 was born in 1963, and entered the work force around 1981, just about the time that the American corporate class began its relentless assault on the living standards of middle class Americans. The real median hourly wage for white men with no more than a high school diploma declined from $19.76 in 1979 to $17.50 in 2014. The Pew Research Center reports that the percentage of Americans in the middle class, defined as an income between two-thirds and double the national median ($42,000 to $126,000 for a family of three), has declined from 61% in 1971 to 50% in 2015.

Of course, some of these economic trends have occurred in other developed countries as well, but the U.S. has a less adequate social safety net and has neglected its infrastructure. Case and Deaton note that most workers in the U.S. have been forced into defined-contribution retirement plans, while in other industrialized countries, defined-benefit plans are the norm. Defined contribution 401(k) plans shift all of the risk of stock market losses onto the employee. The average wealth of middle-income families declined from $161,000 in 2007 to $98,000 in 2010, where it still stands today.

I realize Case and Deaton have documented distress among middle-aged whites, while terrorists, both white Christian and Muslim, are usually (but not always) younger. My argument assumes that increasing mortality among 45-to-54-year-olds is a cumulative result of economic stress that began at an earlier age, and that anxiety about the future is spreading to younger generations. For example, a poll by Harvard’s Instiute of Politics found that 48% of 18-to-29-year-olds believe that the “American dream” is “dead,” while 49% think it’s “alive.”

Needless to say, terrorism is not the only way inequality contributes to a more dysfunctional society. Research is badly needed on the relationship between economic stress and acceptance of the appeals of fascist demagogues. As Harold Meyerson points out, the increase in the death rate and the rise of Donald Trump “share some common roots: a sense of abandonment, betrayal and misdirected rage.”

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Deep Background