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According to a well-accepted principle of , those with a rosy view of the world live to enjoy a ripe old age.  It might make sense to you that the happy have a long life because they have few cares to weigh them down.  Even in the face of stress, crisis, and other threats to their well-being, their constant means that they can look problems in the eye and not be demoralized.  Their cardiovascular, immune, and even nervous systems should go humming along devoid of all of the toxins that can harm the body. 

From your own perspective, though, does it seem like a done deal that the people you know who’ve lived the longest actually were ensconced in a rose-colored haze?  What about the people you’ve known whose lives were cut short?  Were they necessarily unhappy?  Can happiness be the true distinguishing factor between the have’s and have-nots in the longevity game? 

Questioning the considered of happiness’s relationship to longevity, University of Melbourne’s Bruce Headey and Jongsay Yong (2019) examined the data from two very large, long-term panel studies conducted in Germany and Australia to explore what they regarded as anomalies in some of the happiness-longevity studies.  According to this international team, the relationship cannot be as simple as prior researchers have claimed. 

Consider the role of health.  Perhaps, as Headey and Yong point out, people who are fated to die younger than their age counterparts may be unhappier because they are suffering from poor health.  Happy people live longer because they don’t have the chronic conditions that shorten life, as the authors note somewhat sarcastically, “unless we are to believe that happy people stay alive by sheer will power” (p. 717).  also needs to be factored into the equation.  One prior study, the Terman study of the , reported some years ago that it was the actually the happiest people who died at younger ages.  Their early deaths had nothing to do with happiness per se, but with the factors that led to their demise.  As it turned out, the ill-fated happy people had been carefree but reckless as children.  Lower in the personality trait of , they took fewer preventative measures, and therefore met an earlier death than the less cheerful but more careful health-conscious.  Their cheerfulness was matched with the poor habits of , drinking too much, driving too fast, and not complying with health treatments.  They died not because they were too happy but because they failed to guard against these threats to their health. 

Because healthy people live longer, barring any random causes of death, they are the ones left standing when the less healthy members of their generation die off.  Indeed, in any study of aging, no matter what the topic, there will be a dropping out of the population of people who in some ways lack the “right stuff.”  In addition to being careless, they may have inherited unhealthy , made decisions that placed them in harm’s way (such as engaging in risky leisure pursuits), or have been subjected to harsh early environments that affected their ability to survive.  With them gone from the population, the remainder now will appear to be in better shape even though, in reality, they themselves never changed.  As Headey and Yong state, “because those whose health seriously declines also suffer a decline in life satisfaction, it may seriously results in favor of finding a positive link between life satisfaction and longevity if the last few years of life are included” (p. 714). 

Another issue the German-Australian researchers raise is the possibility that the previously-reported happiness and longevity relationship assumed what’s called linearity.  If this assumption were true, happy 10-year-olds will become equally happy 90-year-olds.  However, from their review of the literature, the authors conclude that “people with low levels of life satisfaction die young but otherwise life satisfaction appears to be unrelated to longevity.  There is no evidence that even very high life satisfaction individuals live longer than people who report average levels” (p. 714). 

The data available to Headey and Yong came from two separate longitudinal studies conducted in Germany and Australia that allowed them to examine this potentially non-linear relationship.  The German panel was first tested in 1984 with a sample of 12,541 individuals.  Followed on a yearly basis, by the time of the last wave of testing, the sample had grown to over 60,000 due to the continued addition of the new family members from the original panel.  The Australian study began in 2001 with nearly 14,000 participants and with the addition of new family members and new sample members, grew to 17,606 by 2012.  By the last follow-ups, the samples had lost to death 4,716 participants (Germany) and 1,274 (Australia). 

Additionally, the research team took out, to some extent, the role of selective survival of the happiest.  This statistical problem is more complex than you might imagine, as it turns out.  You can’t test people who aren’t alive, so instead, you have to approximate how they may have scored if they had been providing their happiness ratings to the end of the study.  The alternative is to remove those who ultimately died from the scores of previous years so that the remaining data represent the people who actually show the longevity “dividend.” 

The actual life satisfaction was not an ideal one, in that it was based on a single question with a 0-10 rating scale.  However, it served the purpose of allowing the research team to build a “quasi-lifetime” life satisfaction score representing the average of the years for which the rating was obtained from each participant (with a minimum of three ratings across testings).  Furthermore, to correct for the possibility that life satisfaction’s late-life ratings can reflect changes due to ill health, the researchers eliminated ratings from the last three years of a person’s life, if that person had died.  With these average scores in hand, Headey and Yong divided all panel members into three groups: High lifetime, medium lifetime, and low lifetime life satisfaction.  Adding further to their model, the research team included the controls of health, disability status, , and a number of socioeconomic measures.  Age became used as the “time duration variable” in the model.  The older you are, in other words, the longer you have endured across time.  Finally, the panel data included the so-called “behavioral choices” of physical exercise, involvement in a , and smoking.  Religious attendance was added to the model based on prior research showing that people who attend some type of regular religious services live longer (possibly due to the social support they receive). 

To test the age-happiness relationship, the authors used “survival analysis” which calculates the probability of an individual surviving over time according to a function known as the “hazard ratio,” which shows the chance of dying at time “t” plus the variable “delta.”  With this method, those other controls could be added to the equation to determine which factors increase or decrease the odds of dying at time “t” plus “delta.”  Participants were considered to be “at risk” of dying when they provided their first life satisfaction rating, and “exiting” when they actually died. 

With all controls in place, then, the authors were able to calculate the relative risks of dying for those three life satisfaction groups.  As they predicted, the age-longevity relationship was not in fact linear.  People in the low life satisfaction group died at earlier ages than those in the other two groups, even with the controls in place.  Yet, as the authors suggest from their analysis “many (perhaps all) of these additional controls could be partly consequences of life satisfaction, not just causes” (p. 728).  After that point, happiness, as the article's title states, "makes no difference."  Interestingly, once life satisfaction is treated as a “cause,” in a sense, the late-life dip in life satisfaction the authors expected more or less disappeared. 

To sum up, the Headey-Yong study falls into the category of “don’t believe everything you read” about happiness.  If you’ve survived past the early period at which low life satisfaction would have led to your demise (which you obviously have), the chances are good that your happiness, if not your fulfillment, will set you on a healthy long-term course.