Article Text


Economics, demography, and epidemiology: an interdisciplinary glossary
  1. J A Tapia Granados
  1. Correspondence to:
 J A Tapia Granados
 The University of Michigan, Institute of Labor and Industrial Relations and School of Social Work, 1111 East Catherine Street, Ann Arbor, Michigan 48109-2054, USA;


This glossary focuses on the “borderland” between demography, economic history, economic theory, and epidemiology

  • business cycles
  • demography
  • economic history
  • economics
  • social epidemiology
  • glossary

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When different fields of inquiry have been separately cultivated for a while, the borderland between them often provide fertile ground for new investigations. Allyn A Young, 1924

It is a basic tenet of epidemiology that the conditions in which people live and work are important predictors of health outcomes, including the incidence and timing of specific disorders, injuries, disabilities, and death. Today epidemiology, demography, and economics are distinct fields with few overlapping areas, but the three disciplines once had common roots—in political arithmetic, political economy and such authors as William Petty, John Graunt, Thomas Malthus, and Frederick Engels. From its beginnings in the works of Johann Peter Frank, Louis Villermé, and Rudolph Virchow, the interactions of living and working conditions with health, disease, and mortality issues were a primary concern in the field of public health. During the 20th century epidemiological research has primarily focused on particular effects of the natural, social, and economic context (nutrition, income, education, social class, occupational exposures and behaviours, atmospheric pollutants, etc) on health, risk of disease, and mortality. Today there is a growing recognition of the importance of macroeconomic influences on health.

The focus of this glossary is the “borderland” between the fields of demography, economic history, economic theory, and epidemiology. The terms defined are drawn from publications that focus on the influence of the economy as a whole on health and mortality—or vice versa. However, despite their significance for epidemiology and health policy, many economic terms like “GDP”, “economic growth”, or “sustainable development” are not included because they are beyond the scope of this glossary.

Though epidemiologists often diverge on theoretical approaches and methodological nuances, there are few or no disagreements about basic epidemiological facts, methods and theories. No epidemiologist today defends the miasmatic theory or the causation of mental illness by the influence of the moon. Demography, which originally arose from a Malthusian background with strong emphasis on theories and mathematical models, often taken from economics, has recently developed into a largely empirical discipline, where checking the data can quite straightforwardly solve discrepancies. In economics however the situation is quite different, because not only the approaches but also the answers to basic problems depend on the theoretical orientation. For this reason this glossary also includes entries referring to the major currents of economic thought—neoclassical, Keynesian, Marxian, and ecological. Of course, even that these and not others are the main currents of economic thought would itself be matter of dispute among economists. In entries corresponding to economic concepts references are general and specialised works are not cited.

Terms appearing in small capitals are defined in other entries of the glossary.


See business cycle


According to the agricultural economist Esther Boserup, historically, high population density often led to the adoption of technical innovations and subsequent higher productivity in agriculture.1 In economic history or agricultural economics the term Boserupian is applied to effects or processes referring to a rise in productivity due to technical progress stimulated by population increase. McKeown2 criticised the Boserupian paradigm because the role it attributes to population induced technological change in the determination of food availability leaves population size itself as an undetermined variable, so that the change in population density is supposedly attributable to fortuitous causes such as infectious diseases.


Since the 1970s, Harvey Brenner3–5 has maintained that recessions have an impact on population health, increasing both mortality (general mortality, cause specific mortality attributable to cardiovascular disease, infant mortality, etc) and morbidity (as measured for instance by the incidence of alcoholism, hospitalisations in mental institutions, etc). A number of authors6–10 have criticised Brenner’s contributions. Critiques have included the limitations of analysis based on time series of only a few decades—with very low statistical power—the controversial methods to detrend the series, and the contentious use of lags. Indeed, Brenner has never been very clear in stating the relation between the business cycle and mortality. He referred to rising unemployment as leading to an increase in mortality, but he also mentioned “peak lags between unemployment and mortality rates[that] are two to three years in many industrialized countries” and also “adverse effects of rapid economic growth on mortality.”4 As “on average, economic cycles tend to be 4–5 years in length” and as there is a “classic 2- to 3-year lag in mortality after the peak in the unemployment rate (...) the zero-lag relationship between unemployment and mortality rates is actually inverse”.5 This means, briefly, that mortality increases when unemployment decreases—that is, that mortality is procyclical, which Brenner has never explicitly accepted. Indeed he has also asserted that economic recession “as measured by the unemployment rate, and/or by the business failure rate (...) is positively related to mortality over 0–10 and 1–7 years, respectively”.5 It is not clear what is the appropriate lag length to be considered and how a fixed-lag effect of unemployment overlapped on a non-periodical business cycle of roughly four to five years would consistently produce mortality peaks coinciding with economic booms, and mortality troughs coinciding with recessions.

Though Brenner’s model of the relation between business cycles and mortality has been widely criticised, it has been around for the past 30 years and it is still cited, usually as evidence to support the need for expansionary economic policies. (See also business cycles, eyers stress model, and unemployment.)


Since the early industrial revolution it has been observed that market economies show a succession of periods of upturn and downturn of business activity that have been called business cycles (industrial cycles and trade cycles are synonymous terms). The phase of increasing or accelerating economic activity of these “cycles” has been called “boom”, “expansion” or “prosperity”, while the phase of decreasing, contracting or slowing business has usually been referred to as “slump”, “downturn” or “recession” when mild in intensity, “economic crisis” or “depression” if the deceleration of the economy is significant.11–13 Because of the irregularity of successive phases of expansion and contraction of the economy, the term “business cycle” has been much criticised and often replaced by “business fluctuation” or “economic fluctuation.” Still business cycle has continued to be used and is the standard term in economic literature.14 After the second world war, it was believed that Keynesian theory would provide the appropriate tools necessary to minimise these fluctuations. But strong business fluctuations re-emerged in the 1970s and economic turbulence has been frequent in recent decades throughout the world.


Variables used to characterise the phases of the business cycle. Variables that fluctuate directly with the economy increasing when business expands (decreasing when the economy contracts) are called procyclical indicators (for example, growth rate of GDP, indices of industrial production, employment volume and rate, wages). Those in inverse relationship with the economy, increasing when the economy contracts, are called countercyclical—or rarely, anticyclical (for example, business failure rate, unemployment). Variables that do not correlate with business fluctuations are called acyclical.11–15


See business cycles


See easterlin hypothesis


See business cycles


This term refers to the transformation of a society from high levels of fertility and mortality to low levels of both. The term usually implies that the drop in mortality occurs before the drop in fertility so that the transition includes a period of rapid population growth. The terms fertility transition and mortality transition refer respectively to the fertility and mortality components of the demographic transition.16,17

In the original conceptualisation the demographic transition was considered to be a consequence of the transformation of society from a traditional to a modernised state through economic growth and industrialisation.16 Modern authors however tend to consider the causes of economic growth as distinct from those of mortality reduction,18,19 with women’s education and improvement of status playing an important part in the fall of fertility. The term epidemiological transition usually applies to the qualitative change in major causes of death associated with the demographic transition, with a large reduction in infectious diseases or “diseases of poverty”, which are replaced as major causes of death by non-communicable diseases or “diseases of affluence”.2


See population growth


See population growth


Other things being equal, the size of a birth cohort tends to have a negative effect on the social and economic fortunes of the members of that cohort. According to this demographic hypothesis, also known as the “cohort size hypothesis”—stated by Richard Easterlin in 1980,20— a rise in birth rate would impact negatively on social and economic outcomes through “crowding mechanisms” operating in the family, the school and the labour market. Large cohorts would imply on average a larger number of siblings, less parental care, and school overcrowding, with reduced chances of educational attainment. The large cohort should subsequently be exposed to reduced opportunities in the job market, raised probability of unemployment, and the associated high risks of inadequacy, frustration, disproportionate consumption of alcohol, and higher crime and suicide rates. As the bad fortunes of a large cohort will reduce fertility when that cohort reaches reproductive age, the consequence will be a fall in cohort size and a new cohort with improved opportunities. The succession of cohorts alternating in size will tend to produce cycles in fertility also impacting a variety of social and economic outcomes.20,21

The Easterlin hypothesis does not refer to what demographers and epidemiologists call cohort effect (or “generation effect”),22 which depends on specific exposures determined by a unique environment coinciding with the life span of the cohort. Conversely, the cohort size hypothesis has nothing to do with the particular exposures of a given cohort. Since its origin almost three decades ago empirical research on the Easterlin hypothesis has produced mixed results, with early research apparently disproving the hypothesis and recent studies producing some direct or indirect empirical support for it.23,24


A recently developed field concerned with ecological issues—flows of matter and energy implied by the economic processes of an economy that is viewed as a subsystem of a larger finite global ecosystem—, that have been largely ignored by other schools of economic thought.25 Nicholas Georgesçu-Roegen may be considered its founder.26


See business cycles


See demographic transition


In the late 1970s Joseph Eyer6,27–30 outlined a model in which stress occupies a central role as a mediator of influences generating a procyclical oscillation of mortality. In Eyer’s model, during periods of economic expansion increases in the consumption of toxic substances (alcohol and tobacco), surges in work pace, work time and overtime, and decreases in time and opportunity for social intercourse (with the consequent deterioration of social support) result in increases in levels of stress and diminished immunity, leading to acute cardiovascular disease and microepidemics of mild infectious diseases raising mortality among persons with chronic disease. Moreover, during business expansions high work pace and increasing business-related and recreational traffic raise the incidence of industrial injuries and traffic fatalities. Recent research has provided new evidence on the procyclical oscillation of mortality31–33 and a number of pathways34,35 linking business upturns to behavioural changes or exposure modifications that have or may have significant impacts on health as suggested by Eyer’s model.


See demographic transition


An ambiguous term that has been applied to (1) the escalation in life expectancy associated with the mortality transition36; (2) the role of cultural, social, and behavioural determinants of health in the mortality transition37; (3) the evolution of morbidity levels during the historical decline of mortality (also called morbidity transition).37


See business cycles


System of economic ideas of John Maynard Keynes (1883–1946). In the 1930s, when unemployment was massive throughout the world, Keynes rejected the principle of classical economics that market economies naturally tend to equilibrium. He claimed that in capitalism there is a persistent tendency to insufficient solvent demand for the economic output, which results in overproduction and unemployment. According to Keynes, economic depressions can and must be resolved by active governmental interventions in the economy. In the 1950s Keynes’s ideas were combined with those of the old classical school in Samuelson’s “neoclassical synthesis”, but the synthesis did not survive to recent decades, given that most economists have for the most part rejected or ignored Keynes’s basic message—the need of government stimulation and regulation of the economy to avoid slumps. Today, Keynesian economics or Keynesianism refers historically to the ideas of Lord Keynes, or to a variety of present economic orientations, from the neo-Keynesian and new Keynesian, very close to the neoclassical school, to the post-Keynesian, still backing strong regulations and active economic interventions of governments.38–40


Macroeconomics, initiated by the Keynesian school, refers to the analysis of the economy as a whole, looking at aggregate variables such as national output (measured by gross domestic or gross national product), national or regional unemployment, inflation, etc). Microeconomics deals with individual economic “agents”, of which firms and consumers are the key ones in neoclasical economics. In contrast, Marxian theorists focus on labour—workers subjected to wage labour— and capital—business owners receiving profits. As macroeconomic conditions refer to the aggregate state of the economy, business cycles can be conceptualised as recurring and roughly cyclical changes in macroeconomic conditions.


In An Essay on the Principle of Population as it affects the future improvement of Society, with remarks on the Speculations of Mr. Godwin, M. Condorcet, and other writers, Thomas Malthus (1766–1834) upheld the idea that resource scarcity was the limiting factor arresting population growth. In so doing, he argued strongly against thinkers claiming that the human lot could be improved. Both Godwin and Condorcet had rejected Adam Smith’s idea that individual selfishness led to general good and proposed that society could be improved by abolishing private property.40 Speculating in his essay on why a rapid increase of the human species had not occurred, Malthus answered that “a foresight of the difficulties attending the rearing of family acts as a preventive check, and the actual distresses of some of the lower classes, by which they are disabled from giving the proper food and attention to their children, act as a positive check to the natural increase of population.”41 The positive check resulted basically in early death because of hunger and epidemics. The preventive check would make people delay marriage or never marry at all, so reducing fertility and population growth. Although at the end of his life Malthus emphasised that in modern Europe “the principal check which at present keeps the population down to the level of the actual means of subsistence is the prudential restraint on marriage,” he had previously stated that this preventive check would come into play very slowly, therefore implying that high mortality due to scarcity would be the regulating mechanism balancing human needs with natural resources in most periods of history. Any improvement in living conditions in the short term would generate population growth and “overpopulation”, eventually checked by the subsequent increases in death rates because of overuse of resources.40,42

In the two centuries after Malthus food output grew faster than population in most countries. Present famines are usually considered the consequence of lack of purchasing power of poor people, not lack of food availability. However, among authors in different fields43,44 the view is common that the rapid increase of human populations from the 18th century resulted largely from improved nutrition, and that in the 20th century, for the first time, “numbers and resources were in reasonable balance, so that the Malthusian adjustment through high mortality no longer operated”.45 Today the effects of worldwide industrialisation, coupled with enormous population growth in the last century, have raised the possibility of severe impacts of human activity on nature, such as significant depletion of natural resources and global warming that could easily trigger “positive checks”.44 Georgesçu-Roegen, often considered a founder of ecological economics, once said that Malthus had not been “Malthusian enough”.46


In the system of historical economic, and social ideas of Karl Marx (1818–1883), capitalism, like slavery or feudalism, is a transient stage in history. According to Marxian theory, the basic economic drives in capitalism—profit production and competition resulting in capital accumulation—make growing numbers of people redundant through the substitution of machines for human labour, and lead to increasing concentration and centralisation of capital with the continuous absorption of geographical regions and spheres of life into the realm of commodity production. In the Marxian view profits arise from surplus value created by workers in production, and since profits and wages, other things equal, are in inverse relation, an antagonism is established between those who live on wages (the working class) and those receiving profits (the capitalist class). Induced by the internal dynamics of capitalism, recurrent falls of profitability result in repeated depressions (crises) and escalating social and economic breakdown that will eventually lead to a classless society—or to barbarism.47 Marx viewed most economic theory of his time as apologetic for capitalism. Today, Marx’s ideas are considered by neoclassical economists as foreign to economics and many authors of Marxian provenance classify themselves under the label of political economy.


For Thomas McKeown the slow population growth before the 18th century was mainly attributable to food scarcity, and the rapid increase from that time was largely a result of improved nutrition.2,45 For McKeown the basic reason for the decrease in mortality due to infectious disease in Western Europe during the 18th and 19th centuries was the increase in host resistance to communicable disease, due to the improvements in immunity accompanying better nutrition. Though McKeown did not reject the role of hygiene and sanitary measures in the decrease in mortality, he considered them as playing a very minor part compared with nutrition. McKeown’s nutritional theory has been criticised on the grounds that there is no evidence supporting an improvement in nutrition during the period of large mortality reductions while, on the other hand, there were many clear improvements in public health and urban sanitation that necessarily impacted on population health.19,48


Historically, people living in large numbers in high density urban areas have had an epidemiological advantage over scattered peoples living in low density areas. While most people living in high density populations are immune to infectious diseases they were exposed to in childhood, most people in low density populations are susceptible to those diseases, so that explosive epidemics arise as soon as there is close contact among individuals from both sources. This law, first described by the historian William McNeil,49 may have played a substantial part in historical phenomena like the expansion of Middle East civilisations, the conquest of America by the Europeans after Columbus’ arrival, and the explosive epidemics often triggered in isolated peoples by the arrival of European explorers.50


See health transition


See demographic transition


Also known as marginalist or standard economics, and rooted in the ideas of Adam Smith (1723–1790) and the classical school, neoclassical economics is at the present the dominant school of economic thought. The models of neoclassical economics are based on methodological individualism (that views society as just an aggregate of individuals) and behavioural assumptions for firms (maximising profits) and consumers (maximising utility). Neoclassical economics posits that the market economy (referred to as “capitalism” by other schools) naturally tends to equilibrium, so that economic problems are attributable to influences from government interference or regulations, union activity, weather, or other factors disrupting the efficient functioning of markets.40,51,52 Though Keynes rejected basic tenets of the classical school, in the 1950s Paul Samuelson combined the ideas of the old classical school with Keynes’s theory in his “neoclassical synthesis”, in which the need for some government influence to regulate the economy was accepted. The synthesis did not last long however and in recent decades the predominant orientation in neoclassical economics (monetarism) has all but totally discarded the Keynesian system. (See also keynesian economics, structural adjustment and unemployment.)


See population growth


See structural adjustment


See mckeowns nutritional determinism


Population dynamics is a basic concern of demography. The age and sex structure of the total aggregate of people living at a particular time in a given area are the demographic variables impacting on population change, jointly determined by the rates of fertility, mortality and migration. The Malthusian view of population growth as the source of hunger and social misery was rejected by socialist thinkers, who upheld that the trend to produce “relative surplus population”—that is, unemployment—was a specific feature of capitalism.53Neo-Malthusianism, which claimed that population growth is a major cause of poverty, had a revival in some European countries in the last decades of the 19th century, and was adopted by conservative thinkers and some anarchists. However, in the early decades of the 20th century the decrease in fertility rates in many European countries and rising nationalism worried by the survival of particular nations or races raised pro-natalist movements and removed concerns about population growth. Neo-Malthusianism re-emerged once again in the second half of the 20th century, when population growth was considered to produce a demographic trap of poverty and disease in former colonial regions, and authors like Paul H Ehrlich argued that increasing population size was the primary cause of environmental demise—the “population bomb”. Negative population growth in advanced countries, fertility rates quickly decreasing around the world, and the surge in AIDS mortality in many countries where fertility is still comparatively high have shifted today’s demographic concerns toward other areas like aging and ongoing mass. migrations.54


See malthusianism


See malthusianism


See business cycle


In the decades after the second world war, under the influence of keynesianism, many African, Asian, and Latin American countries applied quotas, subsidies, and tariffs as part of import substitution policies to promote industrialisation and economic development, with governments actively financing infrastructure development and public services and intervening substantially in the economy. After several decades with mixed results in social progress, in the 1970s developing economies found themselves largely indebted, often with severe inflation and unemployment. At that time, when Keynesianism was being largely displaced in mainstream economics, and democratic leaders were often displaced by military regimes, structural adjustment (SA) programmes were put in place in most countries of Africa, Asia, and Latin America, promoted by the international financial institutions—World Bank and International Monetary Fund—now working under the paradigm of neoclassical economics and being the only providers of financing for the governments of the developing world. Basic aspects of SA programmes (also referred to as “the Washington consensus” or “neoliberalism”) were currency devaluation, reduction of public spending, removal of subsidies, tariffs and trade barriers interfering with trade, deregulation, privatisation of public firms, and in general, a radical reduction of governmental involvement in the economy. The expected effect of SA was to eliminate the structural deficiencies of developing economies, resulting in a renewal of growth.55,56 The evaluation of the results reached by the application of SA policies is a matter of strong controversy, though there is consensus that the 1980s were a “lost decade” for development in Africa and Latin America. Mediocre or bad results in most indicators of social progress (poverty, unemployment, literacy...) are interpreted by those opposed to SA as implying a failure of these policies, while authors in the orbit of the World Bank and the IMF claim that policies were not properly implemented or interpret the data as showing some improvement that had not been possible without SA. Cuts in financing and delivery of public services and elimination of food subsidies associated with SA programmes often brought severe deterioration of healthcare services, education, and social welfare nets.57 However, evidence of an impact of SA programmes on specific health indicators in the countries of the developing world is not considered consistent even by authors opposed to SA policies.58,59 When the Soviet block collapsed in the early 1990s, SA programmes were quickly applied to Eastern European and ex-Soviet economies that had been for decades under centralised control of governments. The immediate results were sudden upsurges in poverty, unemployment, and social misery. Particularly in Russia and the other ex-Soviet republics, mortality escalated at unprecedented levels and fertility levels plummeted in the first half of the 1990s.60 Many social indicators in the countries of the developing world have stagnated or substantially deteriorated during the 1990s, but the institutions promoting SA continue defending these policies and claiming that they are the best way to reduce poverty.


In the 1920s Dorothy Thomas61,62 showed that mortality, marriage rates, and birth rates oscillate procyclically—that is, rising when the economy expands and falling during recessions. Thomas was probably the first author clearly stating the procyclical character of mortality—that is, the increase of mortality in times of economic upturn. This procyclical oscillation of death rates was called “Thomas’ effect” by Joseph Eyer.6


Economists often divide unemployment into different categories such as frictional unemployment (that during the period between losing a job and getting a new one) or structural unemployment (attributable to long term changes in the economy, for instance railway workers unemployed when railroads are closed because of generalised road transportation).63,64 In each category a larger or smaller proportion is considered to be made up of workers who could work and do consider themselves part of the labour force, but nevertheless choose, for whatever reason, to remain unemployed. This is voluntary unemployment while the rest is involuntary unemployment. The level of (un)employment in a country is considered by standard economics to reflect the interplay of labour supply (which is supposedly higher with higher wages) and labour demand (which is higher with lower wages), so that a high wage level will generate lower demand and larger supply of labour. When workers become jobless they will usually try to find work at their former wage level rather than below it. For these reasons it is often argued that unemployment benefits that are generous or easily available are likely to contribute to voluntary unemployment. If the income from benefits is more (or even slightly less) than the income that could be earned from employment, there is no incentive for someone to take a job when he or she can. These explanations provided by neoclassicaleconomics are partially rejected by keynesian economics and wholly criticised from the point of view of marxian theory.

Many epidemiological studies have focused on the effects of joblessness on health. While cross sectional ecological studies generally revealed higher mortality rates in countries and regions of high unemployment, the longitudinal ecological evidence is controversial. A number of studies through the 20th century6,61,62,65–67 found a procyclical oscillation of mortality—that is, mortality deviating up from trend during times of increased economic activity and low unemployment (only Hexter68 found a countercyclical oscillation of mortality). Brenner also found mortality peaks coinciding with periods of rapid economic growth, but he explained this as a lagged effect on mortality of the previous recession (see brenner hypothesis). In the 1980s some studies69–73 tend to support Brenner’s interpretation, while others7–10,74–77 tend to dismiss the evidence of any relationship between business cycles and mortality. Ruhm and Gerdtham31–33 have recently provided strong statistical evidence of a decline in age adjusted mortality both for all causes and for the major causes of death during recessions (in contrast, suicide mortality has been consistently found to escalate in recessions31,78 and is directly related to the level of unemployment).79,80

A large body of literature shows that in short follow ups of one or two years mortality in the unemployed is higher than in the employed. There has been much debate on whether this association is causal. Issues discussed in the literature81–83 include bidirectional causation (with both ill health promoting loss of the job and joblessness inducing disease), mediating factors (unemployment causing reduction of income, and this in turn worsening health), and confounding (marginality or poor social adaptation causing both bad health and job loss). Interestingly, the relative risk of death of unemployed with respect to employed decreases during recessions, when unemployment surges.84–86 This suggests that the mortality differential between unemployed and employed during economic upturns may be driven by selection factors (or reverse causation). Alternatively, the health effects of unemployment may be modified by the context in which unemployment occurs. For example, the stress related consequences of unemployment may be less in a recession context when unemployment is widespread.87 Even assuming an increased risk of mortality in the unemployed, overall the relation between unemployment levels and mortality may be driven by the business cycle effects of working and consumption conditions of the non-unemployed population, always a large majority in comparison with unemployed.


The present version of this glossary has largely benefited from suggestions and criticisms of anonymous referees. Ana Diez Roux helped with editing and comments.


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