Working to Death: Status and Mortality in a Managerial Hierarchy

September 21, 2023 | Blog
Home > Working to Death: Status and Mortality in a Managerial Hierarchy

By Tom Nicholas (Harvard Business School)

This blog post is based upon the author’s article, ‘Status and mortality: Is there a Whitehall effect,’ which will be published in the Economic History Review.


Health gradients inform our understanding of how well-being is distributed in society and the consequences of relative affluence and deprivation. In advanced economies a social gradient exists for almost all causes of death, yet we still need to know more about how inequalities in health arise to determine the most appropriate policy responses. Health gradients for white collar workers are particularly understudied in economic history.

A common assumption in studies of health gradients is their monotonicy across the distribution of social ranks. In a unique and highly-cited set of studies in the epidemiology literature, researchers studied civil servants working in Whitehall, the locus of Britain’s governmental bureaucracy. When controlling for socioeconomic status (SES), those at the top of the hierarchy lived longer than those at the bottom.

The researchers attributed this finding to the psychosocial-stress costs of working in subordinate positions in Whitehall. Biologists have noted similar patterns, although the findings are hotly debated. Poor health can determine societal rank as well as be a consequence of it. The nature of the health gradient may also be mediated by the structure of hierarchies.

Robert Sapolsky’s famous studies of baboons in Kenya found detrimental health outcomes among subordinate males in dominance hierarchies, whereas more recent research by Jordan Anderson and co-authors has identified significant health costs from the pursuit of social status in competitive hierarchies. Leaders in competitive hierarchies face the threat of displacement from below, which affects the social gradient. In the animal kingdom, it is not clear that the Whitehall finding generalizes, and it may even be reversed.

My research studies the “Whitehall Effect” – the inverse association between lifespan and hierarchical rank – in a different setting: corporate America around the time of the Great Depression. Managerial hierarchies had begun to diffuse widely meaning that workers were organized in firms according to their rank.

Using archival data for General Electric, I codified over a thousand employees at the firm in 1930 into a six-level hierarchy from top executives to lower ranked workers. I matched employee records to the 1930 federal census to obtain SES variables, and to death records to construct estimates of the health gradient by rank.

The results show a different gradient to the one found by the Whitehall researchers.  Employees at the top of the managerial hierarchy experienced a relatively lower lifespan. Figure 1 shows evidence of shorter mean or median lifespans among upper-level managers and executives relative to their counterparts from comparable birth cohorts in lower levels of the hierarchy, conditional on survival to at least 1930.

Figure 1. The Lifespan of GE employees.
These figures show the mean or median lifespan of GE employees by birth cohort. GE Upper refers to top managers and executives in Level 1, 2 and 3 of the hierarchy and GE Lower to individuals lower down in Level 4, 5 and 6.
Source: Tom Nicholas, ‘Status and mortality: Is there a Whitehall effect,’ Economic History Review, vol.50 no.1 (2023)


Econometric results show individuals in upper levels of the hierarchy lived shorter lives by 3 to 5 years, compared to individuals in lower levels with comparable ages and SES characteristics. Figure 2 illustrates the probability of an individual in the top layers of the hierarchy surviving relative to an individual in the bottom layers.

Over the life cycle of ages shown, this difference will approach zero at either end (few die relatively early, everyone dies in the end) with a U-shape indicating a lower probability of survival for individuals in the top layers. I find individuals in the second layer of the hierarchy, such as vice presidents, were particularly prone to this mortality penalty.

Figure 2. Survival Probabilities in Upper Relative to Lower Levels of the Hierarchy.
This figure shows estimates of the probability of survival to a given age X in a panel where each individual is associated with 51 observations, one for each age-year. Survival probabilities are measured for upper (Level 1, 2 and 3) relative to lower (Levels 4, 5 and 6) positions in the hierarchy.
Source: Tom Nicholas, ‘Status and mortality: Is there a Whitehall effect,’ Economic History Review, vol.50 no.1 (2023)


One potential explanation is that psychosocial-stress operated in an opposite direction to Whitehall. In a bureaucratic hierarchy, individuals at the top are protected from displacement from below by career ladders and fixed promotion rates. Corporate hierarchies, by contrast, are fiercely competitive. Leaders face stress-inducing challenges to maintain their position at the top.

At General Electric, managerial pressures were particularly extreme in this historical context. Stock market volatility reached a high-point during the Great Depression, along with union activity and worker militancy. General Electric was also famously subject to antitrust scrutiny, which severely impacted managers in the second tier of the hierarchy who participated in collusive practices.

In contrast, workers lower down in the hierarchy may have gained health advantages from General Electric’s generous benefits system and welfare provisions or from higher household incomes as a result of unionization. Although I do not establish a causal relationship between psychosocial-stress at the top of the hierarchy and the health gradient, the data are suggestive of a connection.

Does this mean that the Whitehall researchers were wrong? No, it simply means that their results may not generalize to other settings and hierarchies, highlighting the importance of analyzing the dynamics of health gradients in different time periods and workplace environments. With the increased availability of census data and digitizable personnel records, economic historians are well-placed to explain the drivers of health and mortality gaps in hierarchies, connecting historical research to a central topic in public policy.


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