In 2015, Case and Deaton uncovered an epidemic occurring within a particular birth cohort and ethnicity within America alone. The mortality rate of white Americans aged 45-54 had increased on average by 0.5% a year, compared to its previous continuous downward trend (p.15078). They observed that this increase was a result of self-inflection[1], corresponding with increasing morbidity and pain, which do not correlate with subjective well-being surveys and had been experienced during periods of economic growth. This case study seeks to elucidate why this mortality rate has increased, and why it is restricted – for now – to this particular age group, ethnicity and America along amongst developed countries, which has been overlooked by the majority of academia, policymakers and the media alike.

First, this case-study will outline the major academic debates identifying how to measure well-being, and how despite the improving living standards, according to the modern metrics, this epidemic appears to contradict their representativeness. Subsequently, this case-study will explore the state of the economy, income and health inequalities, as possible explanations for this phenomenon. It will be shown that these inequalities contribute to the rate rise, but cannot sufficiently explicate it. Moreover, this case study will demonstrate that this phenomenon disproportionally affects the less-educated, especially men. Thereafter, this case-study will analyse the impact of the changing composition of the US labour market and will conclude that the changing labour market over the past five decades is the catalyst of this epidemic, which has exacerbated income, health and educational inequalities which produce negative life-satisfaction effects.

Academic Debates

The world is increasingly becoming a better place to live (Kutarna, 2016). Global extreme poverty has fallen in both nominal values and as a proportion of world population, falling from approximately 1 billion people (94% of the then world’s population) in 1820 to an estimated 705 million people (9.6% of the then world’s population) in 2015 (Roser and Ortiz-Ospina, 2017). Global life expectancy has increased from 29 to 71.4 years-old during the same time period (Roser, 2017). The distribution of such success is skewed towards different geographical regions, but all regions have experienced increases in the quality of health (WHO, 2017). In 1820, 42.7% of children died before they reached the age of five, in 2015 this figure has fallen to 4.25% (Roser, 2017). Moreover, there is not a single country since World War II where infant mortality is higher than it was in 1950 (Deaton, 2013, p.56). Dollar and Kraay (2002) demonstrate that “growth on average benefits the poor as much as everyone else in society” (p.219). This has been supported by World Bank data, which exemplifies a clear positive relationship between that Gross Domestic Product (GDP) per capita and a reduction in the populace living in extreme poverty, as well as increases to life expectancy (Roser and Ortiz-Ospina, 2017). From this perspective, it can be argued that there has never been a better time to be alive.

However, such a perception disregards the sociological and psychological aspects of life, stemming from Lionel Robbins’ (1932) proposition that such analysis was irrelevant for economic discussions (pp.81-90). This definition simplifies and restricts the reality of well-being to a form of quantifiable, objective data neglecting significant subjective measures of the quality of a person’s life. Economic theory became axiomatic in its nature (Soros, 1997). In particular, GDP per capita was seen as the key measurement of well-being within a country. Indeed, Abbot et al. (2012) observed that “GDP became the paramount statistic in economics…to show that a country was doing well” (p.238). Economic policy fixated on increasing GDP, neglecting its distribution and the social effects of policy. Figure 1[2] illustrates a weak positive correlation between life satisfaction and GDP per capita, signalling that this could be an appropriate measure in determining the well-being of a society. It is important to note that the Latin American region are just as happy as the ‘West’, despite being substantially poorer. This does not discredit GDP per capita as a measure of life satisfaction, but it does weaken its effectiveness in measuring well-being[3].

Figure 1 Mean life satisfaction and GDP per capita adjusted for Purchasing Power Parity (The Economist, 2010)

Abramovitz (1959) supported this distinction from a theoretical perspective, arguing for scepticism when using GDP as a measure of well-being, as GDP is only an index measure of output (pp.21-2). Indeed, it was never the intention to used GDP as a measurement of well-being. Kuznets, who founded the GDP measurement in 1934, contested that its ability to measure well-being is limited, arguing that it only quantified output and excluded activities outside of the market mechanism (1938, p.3). Furthermore, Kuznets aspired to adjust his calculation to remove the “total elements which, from the standpoint of a more enlightened social philosophy than that of an acquisitive society represent disservice rather than service” (cited in Borowy and Schmelzer, 2017, p.13). Explicitly, Kuznets declared that “the welfare of a nation can scarcely be inferred from a measure of national income” (ibid.). Easterlin empirically demonstrated that despite average income levels acting as a prominent predictor in determining individual happiness, it becomes irrelevant regarding average happiness on aggregate (1995, p.4). This seemingly discordant result, illustrative of the logical fallacy of composition, came to be known as the ‘Easterlin Paradox’. Layard (2005) proposed this was because “people are concerned about their relative income and not simply about its absolute level” (p.45). Oishi et al. (2011) confirm a negative relationship between income inequality and happiness levels (p.1099). Therefore, it can be argued that GDP fails to capture the important facets of everyday life that contribute to life satisfaction.

Since 1998, US mortality rates of non-Hispanic white citizens aged 45-54 reversed its downward trend and is now increasing at 0.5% per annum, despite growing GDP per capita during this time period, while it fell by 2% per year between 1978 and 1998 (Case and Deaton, 2017, p.11). Figure 2[4] illustrates the geographical uniqueness of the US non-Hispanic white mortality rates compared to other developed nations. For the other ethnic groups in America, aged 65 years of age and above, are continuing to experience declines in their mortality rates, although in absolute terms the mortality of the Black populace in America is higher (ibid.). The increase in the mortality rate is rooted in self-infliction, either through drugs, alcohol or suicide (Case and Deaton, 2015, pp.15078-9). This is occurring throughout America, despite various cultural and religious make-up. Figure 3[5] illustrates how deaths by morbidity, poisonings, and suicide have increased since 1998; self-inflected measures now dominate the causes of mortality (ibid.). Moreover, in this particular societal group in America, deaths by poisonings are correlated with deaths by suicides in each American region, indicating underlying social distress (ibid.). The growing distress has not been captured by subjective well-being surveys and contradicts the idea that increases to GDP exert a positive influence on an individual’s well-being in a developed nation. This, therefore, proposes the question: what has driven this geographically, ethnic and age-specific phenomenon, especially as it precedes the global financial crisis of 2007/8?

Figure 2 Comparison of mortality rates for the 45-54 year-olds (Case and Deaton, 2015, p.15079)

Figure 3 Causes of mortality for non-Hispanic whites aged 45-54 between 1998 and 2013 (Case and Deaton, 2015, p.15079)

The Economy

The conventional explanation of the increase in suicide rates, morbidity and pain are one of economic instability and downturn. Cross-country comparisons and historical data support this hypothesis, showing that lower economic activity, and thus lower employment, increasing dissatisfaction with life, suicides and morbidity (Preston, 2007). Figure 4 demonstrates a negative relationship between mortality rates and income levels from a historical perspective, although mortality decreases before incomes rise. It also indicates a positive correlation between the two measures for the ages 35-59 stemming from 2010, despite increases in income for the ages 35-44 in this period, and from 2014 for ages 50-59. Whilst this is the case, it does not discredit economic insecurity influencing an individual’s life satisfaction. Particularly, this generation, born in the 1960s, grew up in a period of a productivity slump, with slower earnings growth meaning cumulatively over time that this generation was the first to discover they will not be better off than their parents’ generation (Chetty et al., 2016, p.9).

Figure 4 The relationship between the median household income and mortality rates of white non-Hispanics by age group (Case and Deaton, 2017, p.59)

The proportion of the population earning more than their parent’s generation has seen a downward trajectory since those born in 1940, falling from just over 90% for this birth cohort to 50% for those born in 1980 – a cataclysmic shattering of the American Dream (Chetty et al., 2016, p.32). There is a clear disparity in the mortality rate changes by ethnicities in America for the ages 45-54, between 1999 and 2013, where non- Hispanic whites have increased by 8.9% compared to decreases in the Hispanic (-19.1%) and Black (-27%) populations in this period (Meara and Skinner, p.15006). Skinner speculates that this was because “the financial floor dropped out from underneath [whites]” whereas “for African-American and Hispanic households things had never been that optimistic and so perhaps the shock wasn’t quite as great” (cited in Stein, 2015). This suggests the increasing deaths by suicide and mortality are rooted in the economic expectations and economic certainty of the individual. It is further supported by the significant differences in economic expectations following the Great Recession: 81% of Black and 74% of Hispanic respondents believed their financial situation would improve, compared to 57% of whites (Taylor et al., 2010, pp.48-9). The perceived economic stability could explain the specific age and ethnicity of the distress in life and their subsequent effects. These events occurred all across the developed world, however, the same effects are not being experienced globally, suggesting that the economic certainty explanation is therefore insufficient, at least ceteris paribus, to explain the rising mortality rates illuminating further social dysfunctions at play (Case and Deaton, 2015, p.15078).

Income Inequality

Kawachi et al. (1997) identified a strong correlation between levels of income inequality, social trust, and mortality rates, further certified by Stiglitz (2013). More recently, Starmans et al. (2017) contest that people are not concerned with economic inequality per se, rather it is the effect of perceived economic unfairness which is confounded with income inequality; they reported that people would rather live in a fair unequal society than an unfair equal society. Figure 5[6] illustrates the average American’s ideal wealth distribution is much more equal than the current situation, with the ideal top 1% share being 33% compared to the actual value of 85%, while the ideal share for the bottom 20% is 11% compared to the actual value of <1%. Moreover, Figure 6 shows the disproportionate average pre-tax income gains progressively from the bottom fifth of the income group to the top one per cent before and after tax, from 1979 to just before and after the Great Recession; in every scenario the top one per cent income change dwarfs every other income group, with the next 19% increasing substantially higher than the bottom 20% and the middle 60%. Wealth and pre-tax income distribution in American society are neither equal nor fair. From this perspective, it is the unequal distribution of income and wealth that has caused the mortality rate to increase. A comparison with Europe echoes this conclusion: in 1970 the share of the top 10% of US earners of total pre-tax income stood at 34%, this increased to just over 47% in 2010, Europe stood at 30% in 1970, increasing to 34% in 2010 (ibid.). The international differences in domestic income inequality may explain why mortality has been increasing in America and no other developed nations. From this perspective, it can be argued that income inequality is causing the distress among middle-aged whites. However, income inequality has risen in other developed nations, which suggests income inequality in isolation is inadequate in explaining the changes in mortality.

Figure 5 The actual, estimated and ideal US wealth distributions (Starmans et al., 2017, p.3)





Figure 6 Change in comprehensive income, by income group and time period (Stone et al., 2016, p.10)

Healthcare

The access and quality of health care services are fundamental factors influencing the mortality rate and the pain experienced. In contrast to other developed nations, America does not have universal health care coverage despite recent expansion (Roy, 2015). In its absence, America underperforms in terms of equity and access to health care, especially when incorporating that their spending per capita is the highest (Davis et al., 2014, pp.7-10). In comparison to European countries, American healthcare policy is relatively liberal in the prescription of painkillers, especially opioids, to alleviate pain which became especially prevalent in the 1990s in coordination with the spike in mortality rates (The Economist, 2016). Painkillers are typically very addictive, and tightening of their availability usually led to individuals turning to heroin, with both products strongly associated with mortality (ibid.; McGreal, 2016; Gomes et al., 2011). This explains some of the increase in mortality rates, especially given its restrictions in different developed nations, but it does not justify why the pain was prevalent in the first place in America, indicating more important underlying factors. Opioids are an accelerant of the mortality rate increase, but not the primary cause, and therefore the quality of healthcare cannot be the key determinant (Case and Deaton, 2017).

In America, self-reported health surveys illustrate health inequality is prevalent along educational inequality. Figure 7 shows a positive correlation between good self-reported health and greater educational attainment. It also shows that self-reported health is deteriorating much faster in recent years for those with an education level below a Bachelor’s (BA) achievement, with far fewer less-educated people reporting excellent or very good health at an earlier age compared to previous years. This is in part explained by differing knowledge, as more knowledgeable people are able to identify the relationship between their health and their behaviour (Kenkel, 1991). This was evident in the case of smoking (Farrell and Fuchs, 1982). However, Kenkel (1991) observed that once differences in knowledge are accounted for, the effects of education on health behaviour remain, implying there are other social aspects which have a greater influence. The educational disparity in health corresponds with the mortality rate; there is a clear negative correlation between educational attainment and mortality rate. As Figure 8 shows, the mortality rate by self-inflection progressively increases significantly depending on whether the individual has a BA, a College Degree, or High School or lower. Not only that, but those with a BA or more have remained roughly constant, or in the case of poisonings slightly higher since 1993, whereas those with a College Degree has increased, but at a much slower rate compared to High School graduates. Moreover, deaths by morbidity and poisonings supersede that of suicide signifying that access to health care is a significant contributor to the mortality rate increase and underlying social/psychological factors which motivate the consumption of drugs and alcohol (Marmot and Wilkinson, 2005; Mirowsky and Ross, 2012).

Figure 7 The fraction of white non-Hispanics reporting excellent/very good health, by educational attainment (Case and Deaton, 2017, p.50)

Figure 8 Mortality rate by self-infliction for white non-Hispanics aged 50-54, by educational attainment (Case and Deaton, 2017, p.50)

The Changing Labour Market

During the late-1970s, the dominance of neoliberalism of the labour market in focussed on flexibility, at the expense of the labourer’s job stability and security through watering down regulations and reducing trade union power (Autor et al., 2006; Donato et al., 1992; Autor, 2010). Concurrently, the dynamics of the US labour market changed, stemming from the increasing rate of automation and globalisation, shifting the US economy from one rooted in manufacturing, to one based on knowledge. Consequently, the dominant employment for the less-educated altered from factory-jobs with the scope of improvements, to the low-paying service sector with limited promotional aspects (Autor et al., 2016; Cocco, 2016). In contrast, the demand for higher-educated people has significantly increased (Holzer, 2015). The cumulative effects of these changes are demonstrated by the relative value of income of High School graduates compared to College graduates: in 1975, a High School graduate’s wage was on average worth 85% of a College graduate’s wage in 1975, falling to 55% in 2014 (ibid.). There is an increasing amount of evidence which suggests that demand for middle-skilled workers is also falling, and as a result, is displacing lower-skilled workers from their poorly paid jobs (ibid.). It is clear that the educational inequality has a significant influence on the income distribution, with the less-educated being monetarily worse-off compared to the College-educated counterparts. This stems from the lowering of demand for lower-skilled workers, and the subsequent insecurity rooted in the neoliberal reformations of the mid-to-late 1970s and 1980s, which severely diminished traditional working class jobs, primarily manufacturing, thereby worsening income inequality.

The changing labour market also impacted the labour force participation rate, which has fallen from 67% in 1997 to 63% in Q1 2017 BLS, 2017). This fall is predominantly dominated by men leaving the labour market: the prime-age[7] labour force rate of men has fallen from 98% in 1954 to 88% in 2016 (CEA, 2016, pp.13-4). Figure 9 shows this fall is inordinately represented by men with an educational attainment of High School or less, from 96.5% in 1964 to 83% in 2014, compared to at least a BA which fell from 97.5% to 94% in the same period. The men who left the labour market were mostly living in poverty showing that it was not a choice through surviving off of different incomes (p.24-5). The male-centric fall in labour participation correlates with the differences between the male and female self-inflicted mortality rate, exemplified in Figure 10, further supporting a link between distress and employment[8].

Figure 9 Prime-age male labour force participation by educational attainment (CEA, 2016, p.13)

The changing labour market composition and dynamics made the mortality epidemic not one of the middle-aged whites, but of the middle-aged white working class. Figure 10 shows the mortality rate from self-infliction has increased substantially, from just under 100 per 100,000 to 184 per 100,000, and from 30 per 100,000 to 100 per 100,000, for men and with an educational attainment of High School or lower respectively; in comparison, the rates for has increased slightly since 1998 for both men and women with a College Degree. Case and Deaton (2017) hypothesise that the poor opportunities in the labour market, especially for the less-educated, is at the root of the epidemic witnessed among middle-aged white Americans due to the subsequent social dysfunction that the inequalities produced accumulate over time (p.2). The poor-paying jobs for High School graduates prevent financial stability, which feeds into social factors, such as the inability to sustain a marriage and engage in recreational activities, in turn translating into social instability (pp.29-34; Semuels, 2017). This case-study further proposes that poor labour market conditions lead to a self-reinforcing cycle: as these conditions worsen, the inability of a worker to remain healthy[9] and productive restricts their ability to enter the labour market, furthering inequalities and the consequences that follow. The dramatic neoliberal shift of the economy since the 1970s, and thus the labour market, is at the root of the health, education and income inequalities present. Therefore, the changing composition of the labour market is the catalyst for the increased mortality rate among middle-aged non-Hispanic white Americans, through the cumulative social dysfunctions that occurred as a result.

Figure 10 White non-Hispanic mortality ages 50-54, by self-inflicted death and educational attainment (Case and Deaton, 2017, p.59)

Conclusion

Policymakers’ neglect of the sociological and psychological influences of economic policy is indicated by the contemporary phenomenon of the reversing of the decline of the mortality rates of middle-aged white Americans since 1998, particularly affecting men. This was as a result of self-infliction: from drug and alcohol abuse, and suicide. This was caused by income, health and educational inequalities, but these inequalities were a symptom of a changing labour market. It has been accelerated by the insurance-based health care coverage and a relatively lax painkiller prescription policy America uniquely encompasses, justifying why this has not occurred in other developed nations. The mortality rate increase disproportionately affected the middle-aged white working class in America, who suffered from a ‘dangerous cocktail’ of dramatic shifts in the labour market since the 1970s. This made the less-educated less employable, rendering those born in the 1960s the first generation to be less affluent compared to their parents. This is the opposite case for Blacks and Hispanics – explaining why it is relevant to this birth cohort and ethnicity. This also exacerbated income inequality which fed into other social factors, preventing social stability of the poorer and less-educated, encouraging the consumption of alcohol and drugs, and increasing their risk of morbidity and poisonings. The changing labour market is, therefore, the primary source of income, health, and educational inequalities, and the resulting increase in the mortality rate.

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-7

[1] Self-inflection is defined here as drug and alcohol abuse, and suicide

[2] Circle size is proportional to population size

[3] It could be argued that GDP influences life satisfaction until it reaches a certain point; Deaton and Kahneman (2010) demonstrated how on an individual level, in America, increasing income improves life evaluation until an annualised value of $75,000, it could be possible that this could occur on aggregate. There is currently insufficient evidence to support this argument.

[4] US White non-Hispanics (USW), US Hispanics (USH), and six comparable countries France (FRA), Germany (GER), the United Kingdom (UK), Canada (CAN), Australia (AUS), and Sweden (SWE) between 1988 and 2013 (Case and Deaton, 2015, p.15079).

[5] Death by poisonings is defined as “accidental and intent-undetermined deaths from alcohol poisoning and overdoses of prescription and illegal drugs” (Case and Deaton, 2015, p.15082). Deaths from diabetes and lung cancer are shown by Case and Deaton (2015) to exemplify how this phenomenon has been overlooked by the media and policy makers.

[6] The further 20% value (0.2%) and the bottom 20% value (0.1%) hold such a small amount of wealth, such that they are excluded from the distribution presented (Starmans et al., 2017, p.3)

[7] Prime-age is defined between 25-54 years-old.

[8] Figure 10 clearly shows a significant disparity between the suicide rate of men and women. There is currently insufficient evidence to definitively certify the cause(s) of this (see, for example: NRC, 2014, pp.339-364), thus it will not be discussed in this case-study.

[9] In the absence of universal healthcare.