According to family lore, my father’s mother, Rebecca Kapalovich, arrived at Ellis Island on the day that President William McKinley was shot, September 6, 1901. Sixteen years old, standing less than five feet tall, slim in build, she had left an impoverished village in Russia to seek a better life. Cousins took her into their tenement flat and she soon began sewing clothes in a dark, airless sweatshop on Rivington Street. She and other immigrants on the Lower East Side were exposed to tuberculosis, diphtheria, and pertussis. Subsistence wages made a healthy diet impossible, and disorders like rickets that stunted growth were not uncommon.
Several years after her arrival, Rebecca Kapalovich married Jacob Groopman, who had also fled the deprivations of tsarist Russia. A compact man, five feet five inches tall, he did heavy work as a manual laborer. Influenced by the socialist ideas of the time, and determined to live a healthier life, my grandparents pooled their small savings with extended family and purchased a communal farm in upstate New York. The environment was more salubrious, with nutritious food available from their crops and cows. My father recalled being given concoctions of fresh milk, whole eggs, and honey (“guggle-muggles”) to fortify his skinny form.
The time on the farm proved short, bankruptcy forcing a return to New York City, where my grandfather, during the Depression, sold apples from a cart in the street. He died in middle age from a heart attack, a typical outcome when there were few treatments for cardiac disorders.
My family’s standard of living rose as economic opportunity began to open to lower classes and ethnic groups once held down by prejudice and limited education. After World War II, federal initiatives like the GI bill allowed veterans to pursue college and graduate study and then get better jobs. Scientific advances such as the development of vaccines against polio reduced the morbidity and mortality of viral epidemics, and the development of numerous antibiotics made the treatment of once harrowing bacterial infections, like the appendicitis that took the life of my aunt when she was a child, a matter of course. In the 1950s, my sister and brother and I had access to modern medicines and plentiful food when we were growing, and grow we did.
In a corner of the bedroom I shared with my brother, my mother made small pencil marks noting our vertical progress. I ultimately reached six foot four and a half, my brother six foot two and a half. (Each of our parents was five foot seven.) Those pencil marks are of interest not only to parents and grandparents focused on the health and well-being of their progeny, but to scholars who seek to assess the state of a society, its productivity, and its distribution of resources.
One of the first academics to seek correlations between measurements of body size, or anthropometry, and social conditions was Adolphe Quetelet.1 A Belgian born at the end of the eighteenth century, he was a prodigy in mathematics, and also studied sculpture and painting, published poetry, and coauthored a libretto. Quetelet founded the first astronomical observatory in Belgium in 1826, but soon turned his attention from the stars to the study of the human form. When he was recruited to design a national census of the Netherlands, Quetelet, influenced by seminal thinkers in probability theory including Joseph Fourier and Siméon Poisson, established the principle that a random sample from a representative diversified group could be used to estimate the characteristics of a total population. Over the ensuing decades, Quetelet contended that “the study of man” could be aided by the study of averages of physical characteristics, as well as rates of birth, marriage, and growth. These data, over time, might provide insights into social differences between regions and countries. Between 1831 and 1832, he conducted what is believed to be the first study of newborns and children based on their heights and weights, and then extended his survey to adults.
Three years later, Quetelet published a seminal work entitled A Treatise on Man and the Development of His Aptitudes. Part of the book identified the growth spurts following birth and puberty. Quetelet’s ultimate aim was to define the characteristics of the “average man,” and he initially looked to the familiar bell-shaped curve that had been used by scientists to describe natural phenomena. But he had problems fitting people’s heights and weights in a population into such a normal distribution. Quetelet ultimately devised novel formulas to link height and weight, and is credited with providing the calculations for what we currently term the body-mass index, or BMI, the ratio of weight in kilograms and height expressed in meters-squared (thus a measure of weight standardized by height), a key measure of growth and development.2
With this metric in hand, Quetelet and other academics of his era gathered in Brussels in 1853 at the first International Statistical Congress. Among the many projects launched by the meeting was one to prepare a “uniform nomenclature of the causes of death applicable to all countries.” These data could then be linked to body size and the risk of various diseases, as well as social variables like geography, migration, war, and famine. While keen to apply statistics to social science, Quetelet, who still performed exacting astronomical measurements, was alert to the dangers of overinterpreting numbers associated with numerous factors that might contribute to phenomena like crime rates, the incidence of suicide, and intellectual aptitude.
Like Adolphe Quetelet, Robert W. Fogel, the University of Chicago economist awarded the Nobel Prize in 1993, first was drawn to study natural sciences largely based in mathematics.3 In the autobiography he wrote on receiving the Nobel Prize, Fogel attributed his shift to economics and history in part to the story of his family. His parents were immigrants from Odessa and arrived “penniless” in the early decades of the last century. Fogel grew up amid the hardships and widespread pessimism that marked the Great Depression, and as a child was fascinated by the family’s “intense discussions” about the nature of society.
In 1974, Fogel and his colleague Stanley L. Engerman of the University of Rochester published a book about the economics of African-American slavery, Time on the Cross, which argued that the nineteenth-century slave economy was more efficient than previously believed. It was in the economic interests of plantation owners to treat working slaves relatively well in providing food and shelter so as to maximize their productivity. The database used by Fogel and Engerman to make their case was made up of ship manifests and bills of lading for human cargo that listed slaves by name and physical characteristics, including height, that were stored at the National Archives. The book set off an enormous controversy, since it contradicted the prevailing notion that slaves were treated with unthinking brutality. C. Vann Woodward reviewed Time on the Cross in these pages and noted that it marked “the start of a new period of slavery scholarship and some searching revisions of a national tradition.”4 The current use of anthropometry as a discipline to more accurately assess social and cultural practices, in part, grew out of that scholarship.
Over the past three hundred years, there has been an indisputable decline in morbidity and mortality in Europe, the United States, and more recently parts of Asia. In his Nobel lecture, Fogel highlights how this trend toward increased human growth and longevity sharply challenged two classical views of economic history: the catastrophic scenarios of Malthus and the utopian vision of Marx. According to the Malthusian theory of population, any improvements in mortality were postulated to be short-lived: as the population increased in relation to the food supply, the reduction in death due to one disease would be compensated for by death due to some other malady. Marx envisioned continued oppression of workers, until the unstoppable churnings of history sparked revolution that led to a dictatorship of the proletariat built on the ruins of capitalism.
The Changing Body is a synthesis of some five decades of research in demography, economics, medicine, and sociology, and might be viewed as a culmination of the inquiry begun by Quetelet. Written by Fogel with Roderick Floud, a British economic historian and provost of Gresham College, London, Bernard Harris, professor of the history of social policy at the University of Southampton, and Sok Chul Hong, an assistant professor of economics at Sogang University in South Korea, and presented as a textbook, it poses a “very simple” thesis:
The health and nutrition of one generation contributes, through mothers and through infants and childhood experience, to the strength, health, and longevity of the next generation; at the same time, increased health and longevity enable the members of that next generation to work harder and longer and to create resources which can then, in their turn, be used to assist the next, and succeeding, generations to prosper.
The authors introduce the term “technophysio evolution” to represent the proposition that “changes in the size, shape, and capability of the human body since the beginning of the eighteenth century both reflect and illuminate economic and demographic change over those three centuries.” This synergy between technological and physiological improvements, the authors contend, has yielded a unique form of human evolution. The timeframe of a century since my grandparents’ arrival, or even the three centuries that the authors consider in their analysis, is simply too short for mutation and recombination in the human genome to play out in classical Darwinian evolution to yield taller and more robust men and women.
Rather than principles of Darwinian science, The Changing Body invokes a cardinal law of thermodynamics, the conversion of energy into work, as an underpinning of technophysical evolution:
Human beings, from conception to death, take in energy in the form of food and warmth, and expend it in body maintenance, growth, exercise, and work—both physical and intellectual. Greater inputs of energy allow men and women to work longer but also more intensively. In addition, for much of human history, intellectual work has resulted in the invention and innovation of tools which enable men and women to convert their energy more efficiently into outputs, both physical and intellectual. These tools have enabled men and women to transcend the limitations of their own individual physical capacity for work and thus, over centuries, have expanded their productivity—their lifetime output—to an enormous degree.
But the linkage of food energy to productivity and progress, Fogel and his coauthors believe, goes further. Substantial nutrition is essential for human immune defenses that improve the chance of surviving illness, particularly the infectious diseases that plagued earlier centuries. That malnutrition predisposes a person or a population to death from microbial diseases is well established in medicine. And the conception that better-nourished populations will have the energy not only for manual labor but also for intellectual endeavors, strongly argued by the authors, is also a reasonable, commonsensical idea. If you are starving and desperate for food, there is little motivation or time for education and creative work.5
The so-called Barker hypothesis, published in 1989 by the British physician David Barker, is a prominent underpinning of the central conception of the authors: that a fetus deprived of nutrition may be predisposed to diseases that typically appear in adulthood. This view was formulated by retrospectively studying the medical records of adults in the United Kingdom and correlating birth weights with risks for disorders like heart attack and diabetes that occur later in life. The authors write:
Even if malnutrition in childhood is followed by improved economic circumstances in later life, so that there is then no lack of energy for current work and other activity, the earlier deprivation can have long-term consequences.
In The Changing Body, they further argue that increases in average height of men and women can be taken as a reliable measure of the success of different societies, specifically the productivity of their economies, the fair distribution of their resources, and wider access to scientific advances in health care and the workplace.
The voluminous data cited in The Changing Body to statistically support its theses come from observational surveys. These derive information on changes in the heights of military recruits, factory workers, and residents of geographic areas from the 1700s to the present from historical records and other documents, not scientific experiments. No one has conducted (or should) randomized controlled trials to more scientifically assess the impact of factors like dietary nutrients on health and productivity by, say, assigning one group of mothers to a robust diet and another group to limited food. But extreme care needs to be exercised to avoid overinterpreting statistical correlations from data like birth weights and later maladies as indicating causation.
This caveat about confusing correlation with causation is raised by the authors, but the temptation is nonetheless powerful enough for them to draw attention to research that stands on thin etiological grounds. And it is here that the book stumbles. For example, the authors cite a study that showed “that there is a negative association between height and certain causes of premature death, such as prostate cancer, lymphoma, and colorectal cancer.”6 But each of these malignancies is very different in its biology. Moreover, the ages of the patients at the time of diagnosis of each cancer are not similar, and the increased adoption over recent decades of screening tests such as PSA and colonoscopy have changed the incidence of those tumors, resulting in a so-called “lead time bias,” where survival appears to change but in fact only reflects an earlier time of detection.
Rarely are the findings from observational studies of such magnitude that the high degree of correlation in conjunction with solid biological research mitigates the danger of confusing correlation with causation. Cigarette smoking and its correlation with development of lung cancer or emphysema is arguably the best example. In that case, epidemiological studies, complemented by laboratory research on toxins in tobacco smoke, overwhelmingly showed a cause-and-effect relationship.7
By contrast, in 2000 Peter C. Austin, a medical statistician at the University of Toronto, and his colleagues conducted a study of all 10,674,945 residents of Ontario aged between eighteen and one hundred. Residents were randomly assigned to different groups, in which they were classified according to their astrological signs. The research team then searched through more than two hundred of the most common diagnoses of hospitalization until they identified two where patients under one astrological sign had a significantly higher probability of hospitalization compared to those born under the remaining signs combined: Leos had a higher probability of gastrointestinal hemorrhage while Sagittarians had a higher probability of fracture of the upper arm compared to all other signs combined.
It is thus relatively easy to generate statistically significant but spurious correlations when examining a very large data set and a similarly large number of potential variables. Of course, there is no biological mechanism whereby Leos might be predisposed to intestinal bleeding or Sagittarians to bone fracture, but Austin notes, “It is tempting to construct biologically plausible reasons for observed subgroup effects after having observed them.” Such an exercise is termed “data mining,” and Austin warns, “Our study therefore serves as a cautionary note regarding the interpretation of findings generated by data mining, and suggests that conclusions obtained from data mining should be use with a healthy degree of skepticism.”8
The authors’ model of “technophysio evolution” in The Changing Body is most convincing in the dramatic increases in life expectancy in developed nations. They then ask: How long might future generations live?
So far the maximal capacity of human longevity has been restricted by limited diet and lifetime health insults. But human beings may live up to 130 years if they are well fed and if there were no health insults over the lifetime.
The authors note that this estimate is based on the work of Leonard Hayflick, who demonstrated that cultured human cells have a limited capacity for replication, and so eventually enter a phase of senescence (the Hayflick Limit), in which they no longer can sustain life. The limit is presumed to occur because the structures at the end of chromosomes, called telomeres, reach a critical length. Cells in culture derived from normal human fetal tissue (those presumably protected from “health insults” such as ambient radiation) will divide between forty and sixty times before entering the senescent phase. Each mitosis or cell division shortens the telomeres on the chromosomes of the cell, which eventually makes cell division impossible. But again, extreme caution needs to be exercised in extrapolating from cell growth in a laboratory dish to the fate of human beings. And it is difficult to envision a life without any “health insults,” in a changing and sometimes noxious environment.
They are on somewhat firmer footing when addressing cognitive capacity and social factors. “It seems likely,” they write, that “poor nutrition affects labor productivity because it diminishes cognitive ability and the capacity to undertake and benefit from education.” They note that poorly nourished children often start school later, progress through school less rapidly, and do less well on cognitive achievement tests when older. Birth weight was significantly and positively associated with cognitive ability at age eight in a cohort of Britons born in 1946, even after the factors of gender, father’s social class, mother’s education, and birth order were discounted:
On the basis of all this evidence from the modern world, it seems highly likely that populations in the past, with high levels of malnutrition, suffered from low productivity not simply because of diminished physical strength but also because of diminished cognitive ability or intelligence. The relative contribution of these two potential causes of low productivity may be impossible to determine, but they are likely to have reinforced each other.
They recognize that this is “a potentially contentious statement—particularly when applied to differences in stature between and within modern populations.” Thus they emphasize their belief that “all human populations have equal potential which will be fulfilled under conditions of optimal nutritional status—even if that state has possibly never been achieved.”
While The Changing Body is written as a textbook with numerous graphs and equations, the intriguing subject of anthropometry has been examined in popular writing. Stephen S. Hall in his book Size Matters: How Height Affects the Health, Happiness, and Success of Boys—and the Men They Become9 devotes a chapter to his meeting with Richard Steckel, a student of Fogel’s when he wrote Time on the Cross. Steckel is now an economic historian at Ohio State University, and with Hall toured the Smithsonian Institution’s National Museum of the American Indian in Lower Manhattan. They lingered in front of a large watercolor and ink drawing of the Battle of Little Big Horn from the 1880s, painted by Standing Bear, who as a seventeen-year-old had participated in the battle. “While most museum goers (including me),” Hall writes,
predictably search for the likeness of George Armstrong Custer in the tableau, Steckel saw in it a crystallization of all the invisible factors that can contribute to a unique quality of life, and that quality revealed itself in a single characteristic of the figures peopling the painting: their height…. The individual Lakota Sioux warriors appeared to be as tall as, or taller, than their American adversaries.
Steckel attributes their robust form to several factors: the high-protein diet of the Plains tribes; their excellent dental health; the ways their use of horses reduced their work effort, and may also have allowed these tribes to disperse quickly at the first sign of epidemic disease. The Plains Indians also may have benefited nutritionally from their custom of long-term breast-feeding.
Hall points out that height data from the muster roles of Custer’s 7th Cavalry show that the soldiers averaged slightly more than five foot seven in height, an inch or two shorter than the average height of the tribes they fought, using height measures of Native Americans collected in the nineteenth century. Indeed,
the Plains tribes were on average among the tallest people in the world at the time—taller than native-born white Americans, taller than Europeans, taller than virtually any national group for whom reliable data exists.
Although the Native Americans were viewed as “poor,” Steckel and his colleague Joseph M. Prince of the University of Tennessee wrote that “height and health are known to be sensitive to inequality,” and suggested that egalitarian values, a steady food supply, and “social and economic fluidity” allowed these Native American nomads to build a stronger social safety net than their European American contemporaries.” The health and welfare of society, according to Steckel and Prince, may be best gauged not by monitoring numbers such as average income or gross domestic product, but by the communal commitment and collective ability to care for the young, resist disease, and maximize the salutary effects of good nutrition. All these factors help a given society to maximize the genetic potential of its people, and that maximized potential translates into a single salient characteristic: greater average height.
Another prolific scholar influenced by Fogel is the Hungarian-born and American-bred John Komlos, who has created a research center at the University of Munich focused on anthropometric studies. He is featured in Burkhard Bilger’s New Yorker article “The Height Gap,” in which Bilger wrote:
The Netherlands, as any European can tell you, has become a land of giants. In a century’s time, the Dutch have gone from being among the smallest people in Europe to the largest in the world. The men now average six feet one—seven inches taller than in Van Gogh’s day—and woman five feet eight…. From Rotterdam to Eindhoven, ceilings have had to be lifted, furniture redesigned, lintels raised to keep foreheads from smacking them.10
Bilger further observes that “for more than two centuries,” Americans “had been so healthy and so prosperous that they towered above the rest of the world—about four inches above the Dutch, for example, for most of the nineteenth century.” But now, the average American man is about five foot nine—four inches shorter than the average Dutch man.
What may explain the change in comparative growth rate? Bilger turns to J.W. Drukker, a professor of economic history at the University of Groningen, who analyzed databases of Dutch soldiers and their incomes. Drukker found that
Holland’s growth spurt began only in the mid-eighteen-hundreds…, when its first liberal democracy was established. Before 1850, the country grew rich off its colonies, but the wealth stayed in the hands of the wealthy, and the average citizen shrank. After 1850, heights and income suddenly fell into lockstep: when incomes went up, heights went up (after a predictable lag time), and always to the same degree.
The average height of native-born American males has not significantly changed since the middle of the twentieth century. This plateau contrasts with the trends in Europe, where growth increases have continued, dramatically in countries like the Netherlands, which now has on average the tallest European men. Factors that have been considered by way of explanation of static American growth are social inequality, an inferior health care system, and fewer welfare safety nets compared to western and northern Europe, despite our high per capita income. Although our health care system and its long-standing lack of universal coverage is often blamed as a primary factor, we should not jump to this conclusion.
For example, infant mortality rates in 2005, which some consider to be indicators of the success or failure of a nation’s health care system, were 2.4 deaths per 1,000 births in Sweden and 6.8 deaths per 1,000 births in the US.11 This would seem to support the difference between universal coverage in Sweden and millions of uninsured in the US. But in Canada, which has long had a national single-payer system, the infant mortality rate was 5.3 deaths per 1,000 births, more than twice that in Sweden. Social and cultural factors beyond universal health care coverage clearly are relevant to rates of infant mortality.
According to some economic historians, the widening gap between rich and poor in the United States may have caused the growth curve to have flattened and even reversed. One contributing factor may be the American fast-food diet that is causing many to grow horizontally rather than vertically. Fogel and his coauthors write:
Today, overnutrition and obesity are concerns. Inequalities in death, chronic disorders, activity limitation, body size, and access to better nutritional and medical services are still observed among various socioeconomic groups. Thus, eliminating this new type of malnutrition and reducing these inequalities are the American challenges for the twenty-first century.
In fact, the distribution of fast foods that are cheap, filling, and associated with obesity is not uniform. The Centers for Disease Control and Prevention in 2009 noted that “blacks had a 51 percent higher prevalence of obesity and Hispanics had a 21 percent higher obesity prevalence compared with whites.”
In January 2010, the Centers for Disease Control and Prevention published an analysis of the most recent changes in weight, as well as in height, in the United States from the National Health and Nutrition Examination Survey (NHANES).12 The prevalence of obesity in adults, defined as a body-mass index of 30 or greater, was relatively stable over the period of 1960 to 1980. The BMI then jumped, and currently the prevalence of obesity is 32.2 percent among adult men and 35.5 percent among adult women. But obesity does not appear to be increasing at a uniform rate: the prevalence of a high BMI appeared to reach a plateau between 1999 and 2006, except among the most obese.
Floud, Fogel, Harris, and Hong question how meaningful these recent changes in height and weight may be for standard of living, longevity, and productivity. They rightly caution against overinterpreting the fact that Americans, and more recently certain groups in Europe and in Asia,13 have an increasing average BMI. A few decades of data may not be enough to mark a lasting change in “technophysio evolution.”
Early in The Changing Body, the authors state that “there are dangers, but also benefits, in simplification and the use of analogy.” At one point, they write that the nutritional status and the amount of work of one generation “determines” the welfare of the next. But quickly they pull back:
It might perhaps be prudent to replace the word “determines”…by the word “influences” or “partially determines.” …The schema is certainly not put forward as a deterministic model; there are, in its workings, many historical contingencies and also many uncertainties.
That their model has such limits will likely become more apparent as we have access to a century of data from comprehensive surveys like those conducted by the CDC that don’t depend on stitching together historical documents. The authors also consider whether new variables, like climate change, might affect their model. Despite these concerns, the authors place themselves on the side of the “Whig interpretation of history, one of continual progress toward a better society.” That view certainly applied to the experience of my family and others with immigrant roots: America proved to be a place of robust growth in every sense of the phrase. But in view of our often reckless treatment of the environment and ourselves, the question raised at the conclusion of The Changing Body, whether these improvements will continue, is aptly answered by the authors: “We do not know.”
1 See Frank H. Ahnkins, Adolphe Quetelet as Statistician (Columbia University Press, 1908). See also Stephen M. Stigler, The History of Statistics: The Measurement of Uncertainty Before 1900 (Belknap Press/Harvard University Press, 1990); and Garabed Eknoyan, "Adolphe Quetelet (1796–1874)—The Average Man and Indices of Obesity," Nephrology Dialysis Transplantation, Vol. 23 (2008). ↩
2 In 1972, Ancel Keys published a comparative study of indices of relative weight and obesity, confirmed the validity of the Quetelet Index, and named it the body mass index. See Ancel Keys et al., "Indices of Relative Weight and Obesity," Journal of Chronic Diseases, Vol. 25, Nos. 6–7 (July 1972). ↩
3 Fogel was awarded the Nobel Prize, along with Douglass C. North, for "having renewed research in economic history by applying economic theory and quantitative methods in order to explain economic and institutional change." See his autobiography at nobelprize.org; see also Robert W. Fogel, "Economic Growth: Population Theory, and Physiology: The Bearing of Long-term Processes on the Making of Economic Policy," Nobel Lecture, December 9, 1993. ↩
4 Stanley L. Engerman and Robert William Fogel, Time on the Cross: The Economics of American Slavery (Norton, 1995); see the review by C. Vann Woodward, " The Jolly Institution," The New York Review, May 2, 1974. Thomas Haskell of Rice University provided in these pages a summary of the many criticisms by historians and economists of Fogel and Engerman's work on slavery, particularly their extrapolations about causation and behavior from quantitative data that appear to be "startling flights of conjecture." See Thomas L. Haskell, " Were Slaves More Efficient? Some Doubts About 'Time on the Cross,' " The New York Review, September 19, 1974. ↩
5 A famous aphorism from the Talmud, well known to my forebears, captures this observation: Ayn kemach, ayn torah, "without flour, there is no learning." ↩
6 George Davey Smith et al., "Height and Risk of Death Among Men and Women: Aetiological Implications of Associations with Cardiorespiratory Disease and Cancer Mortality," Journal of Epidemiology and Community Health, February 2000. See also George Davey Smith, Martin Shipley, and David A. Leon, "Height and Mortality from Cancer Among Men: Prospective Observational Study," British Medical Journal, November 14, 1998. ↩
7 The cardinal paper setting forth criteria to link correlation and etiology: Sir Austin Bradford Hill, "The Environment and Disease: Association or Causation?" Proceedings of the Royal Society of Medicine, Vol. 58 (1965). See also Jerome Groopman, "Birth Pangs," The New York Times, October 3, 2010, and Jerome Groopman, "The Plastic Panic," The New Yorker, May 31, 2010. ↩
8 Peter C. Austin et al., "Testing Multiple Statistical Hypotheses Resulted in Spurious Associations: A Study of Astrological Signs and Health," Journal of Clinical Epidemiology, Vol. 59 (2006). ↩
9 Stephen S. Hall, Size Matters: How Height Affects the Health, Happiness, and Success of boys—and the Men They Become (Houghton Mifflin, 2006). ↩
10 Burkhard Bilger, "The Height Gap: Why Europeans Are Getting Taller and Taller—and Americans Aren't," The New Yorker, April 5, 2004. ↩
11 The Organisation for Economic Co-operation and Development (OECD), Health at a Glance, 2007; see also T.R. Reid, The Healing of America (Penguin, 2009), pp. 33–34. ↩
12 Katherine M. Flegal et al., "Prevalence and Trends in Obesity Among US Adults, 1999–2008," Journal of American Medical Association ( JAMA ), January 13, 2010. See also J. Michael Gaziano, "Fifth Phase of the Epidemiologic Transition: The Age of Obesity and Inactivity," JAMA, January 13, 2010; and Cynthia L. Ogden et al., "Prevalence of High Body Mass Index in US Children and Adolescents, 2007–2008," JAMA, January 13, 2010. ↩
13 Wei Zheng et al., "Association Between Body-Mass Index and Risk of Death in More Than 1 Million Asians," New England Journal of Medicine ( NEJM ), February 24, 2011. See also Alpana P. Shukla et al., "Body-Mass Index and Risk of Death in Asians," NEJM, June 2, 2011. ↩
See Frank H. Ahnkins, Adolphe Quetelet as Statistician (Columbia University Press, 1908). See also Stephen M. Stigler, The History of Statistics: The Measurement of Uncertainty Before 1900 (Belknap Press/Harvard University Press, 1990); and Garabed Eknoyan, “Adolphe Quetelet (1796–1874)—The Average Man and Indices of Obesity,” Nephrology Dialysis Transplantation, Vol. 23 (2008). ↩
In 1972, Ancel Keys published a comparative study of indices of relative weight and obesity, confirmed the validity of the Quetelet Index, and named it the body mass index. See Ancel Keys et al., “Indices of Relative Weight and Obesity,” Journal of Chronic Diseases, Vol. 25, Nos. 6–7 (July 1972). ↩
Fogel was awarded the Nobel Prize, along with Douglass C. North, for “having renewed research in economic history by applying economic theory and quantitative methods in order to explain economic and institutional change.” See his autobiography at nobelprize.org; see also Robert W. Fogel, “Economic Growth: Population Theory, and Physiology: The Bearing of Long-term Processes on the Making of Economic Policy,” Nobel Lecture, December 9, 1993. ↩
Stanley L. Engerman and Robert William Fogel, Time on the Cross: The Economics of American Slavery (Norton, 1995); see the review by C. Vann Woodward, ” The Jolly Institution,” The New York Review, May 2, 1974. Thomas Haskell of Rice University provided in these pages a summary of the many criticisms by historians and economists of Fogel and Engerman’s work on slavery, particularly their extrapolations about causation and behavior from quantitative data that appear to be “startling flights of conjecture.” See Thomas L. Haskell, ” Were Slaves More Efficient? Some Doubts About ‘Time on the Cross,’ ” The New York Review, September 19, 1974. ↩
A famous aphorism from the Talmud, well known to my forebears, captures this observation: Ayn kemach, ayn torah, “without flour, there is no learning.” ↩
George Davey Smith et al., “Height and Risk of Death Among Men and Women: Aetiological Implications of Associations with Cardiorespiratory Disease and Cancer Mortality,” Journal of Epidemiology and Community Health, February 2000. See also George Davey Smith, Martin Shipley, and David A. Leon, “Height and Mortality from Cancer Among Men: Prospective Observational Study,” British Medical Journal, November 14, 1998. ↩
The cardinal paper setting forth criteria to link correlation and etiology: Sir Austin Bradford Hill, “The Environment and Disease: Association or Causation?” Proceedings of the Royal Society of Medicine, Vol. 58 (1965). See also Jerome Groopman, “Birth Pangs,” The New York Times, October 3, 2010, and Jerome Groopman, “The Plastic Panic,” The New Yorker, May 31, 2010. ↩
Peter C. Austin et al., “Testing Multiple Statistical Hypotheses Resulted in Spurious Associations: A Study of Astrological Signs and Health,” Journal of Clinical Epidemiology, Vol. 59 (2006). ↩
Stephen S. Hall, Size Matters: How Height Affects the Health, Happiness, and Success of boys—and the Men They Become (Houghton Mifflin, 2006). ↩
Burkhard Bilger, “The Height Gap: Why Europeans Are Getting Taller and Taller—and Americans Aren’t,” The New Yorker, April 5, 2004. ↩
The Organisation for Economic Co-operation and Development (OECD), Health at a Glance, 2007; see also T.R. Reid, The Healing of America (Penguin, 2009), pp. 33–34. ↩
Katherine M. Flegal et al., “Prevalence and Trends in Obesity Among US Adults, 1999–2008,” Journal of American Medical Association ( JAMA ), January 13, 2010. See also J. Michael Gaziano, “Fifth Phase of the Epidemiologic Transition: The Age of Obesity and Inactivity,” JAMA, January 13, 2010; and Cynthia L. Ogden et al., “Prevalence of High Body Mass Index in US Children and Adolescents, 2007–2008,” JAMA, January 13, 2010. ↩
Wei Zheng et al., “Association Between Body-Mass Index and Risk of Death in More Than 1 Million Asians,” New England Journal of Medicine ( NEJM ), February 24, 2011. See also Alpana P. Shukla et al., “Body-Mass Index and Risk of Death in Asians,” NEJM, June 2, 2011. ↩