1

The Rise and Fall of Pellagra

in the American South

Karen Clay*

Ethan Schmick†

Werner Troesken‡

This draft: August 2016

Abstract

No other nutrition-related disease in American history caused as many deaths as

pellagra. The by-product of insufficient niacin consumption, pellagra reached epidemic

proportions in the American South, killing roughly 7,000 Southerners annually at its

peak in 1928. We document the rise and fall of pellagra in the American South and

present three main findings. First, pellagra resulted, in part, from Southern agriculture’s

heavy emphasis on cotton, which displaced local food production and effectively raised

the price of niacin consumption. Evidence for this proposition derives in part from the

arrival of the boll weevil. Although the boll weevil reduced Southern incomes and

cotton production, it was also associated with increases in local food production and

sharp reductions in pellagra. Second, pellagra was largely eliminated through voluntary

fortification of cereal-grain products starting in 1937 and a series of state fortification

laws passed in the 1940s. These laws, for the first time in Southern history, broke the

strong positive correlation between cotton production and pellagra. Third, exposure to

early-life interventions that reduced cotton production and/or increased niacin

consumption were associated with improved stature and wages. These findings have

important implications for our understanding of the economic history of the American

South and economic development in general.

* Contact: Karen Clay, Associate Professor of Economics and Public Policy, Carnegie Mellon

University, Heinz College, 5000 Forbes Avenue, Pittsburgh, PA 15213. Email:

kclay@andrew.cmu.edu † Contact: Ethan Schmick, University of Pittsburgh, Department of Economics, 4901 Wesley W.

Posvar Hall, 230 South Bouquet, Pittsburgh, PA 15260. Email: ejs83@pitt.edu ‡ Contact: Werner Troesken, Professor of Economics, University of Pittsburgh, Department of

Economics, 4901 Wesley W. Posvar Hall, 230 South Bouquet, Pittsburgh, PA 15260. Email:

troesken@pitt.edu

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1. Introduction

While virtually unheard of in the United States today, no other nutrition-related

disease in American history has caused as many deaths as pellagra. The by-product of

insufficient niacin consumption, pellagra reached epidemic proportions in the American

South during the first half of the twentieth century, killing roughly 7,000 Southerners

annually at its peak in 1928 (Bollet 1992).1 Put another way, at its peak in 1933, malaria

killed around 4,500 Southerners annually, or only two-thirds the number of people

killed by pellagra at its peak.2 If one looks at the incidence of pellagra, the data are even

more striking. According to one estimate, the case fatality rate for pellagra was only

around 3% (Goldberger 1928). Thus, it is possible that in 1928 there were approximately

230,000 cases of pellagra in the United States, which is equivalent to the population of

Atlanta at the time. In places where pellagra was endemic, it was estimated that around

20 percent of all households had at least one person sick with the disease (Goldberger

1928). While pellagra was not as pervasive as hookworm, which infected around one-

third of the Southern population, it is important to remember that pellagra is an extreme

indicator: one need not have developed a full-blown case of pellagra to have been poorly

nourished, and the high incidence of pellagra is suggestive of widespread malnutrition

in the South (Etheridge 1972, Youmans 1964).

Although there is a small literature on pellagra in the American South, that

literature is mostly qualitative and has not been subjected to formal hypothesis testing.

As a result, our understanding of the origins and effects of pellagra is incomplete and

predicated on a limited evidentiary base. In this paper we document the rise and fall of

pellagra in the Southern United States by conducting a series of falsification exercises to

test the central predictions of the existing historical literature. Additionally, we extend

the literature by offering and testing new hypotheses on the long-term effects of early-

1 The Mortality Statistics of the United States report 6,824 deaths from pellagra in the year 1928. 2 The Mortality Statistics of the United States report 4,678 deaths from malaria in the year 1933. This

number is likely overstated since in several years it is reported that the term malaria “is used

somewhat loosely in some sections of the country” and that this “undoubtedly has much to do

with some of the higher rates recorded” (Mortality Statistics of the United States 1924; pg. 25).

3

life exposure to high pellagra environments. Our results do not call for a wholesale

revision of the prevailing understanding of pellagra in the American South, but they do

bring to the fore economic and nutritional mechanisms that have important implications

for our understanding of the American South in particular, and cash crop economies in

the developing world more generally.

We focus on three sets of questions. First, what were the origins of pellagra, and

why was it so pronounced in the American South? Existing historical accounts suggest

the disease stemmed from the Southern production of cotton. According to the standard

logic, cotton displaced local food production and drove poor Southern farmers and mill

workers to consume milled Midwestern corn, which was relatively cheap but was also

devoid of niacin (Park et al. 2000, Goldberger et al. 1920, Rajakumar 2000). Second,

pellagra rates plummeted during the mid-twentieth century. What drove this sharp

decline? Existing historical accounts attribute the eradication of pellagra to a series of

state laws passed during the 1940s mandating breads and grains be fortified with niacin

and other nutrients (Humphreys 2009, Park et al. 2000). Third, we ask a question that the

existing qualitative literature has left unaddressed: what were the effects of pellagra, and

nutritionally deficiencies more generally, on the long-term welfare of Southerners?

We begin our analysis by searching for systematic evidence that cotton

production displaced local food production, which in turn limited the availability of

nutritionally-rich locally-sourced foods and discouraged adequate consumption of

nutrients, such as niacin. Consistent with the prevailing historical understanding, we

find that in times and places of high cotton production, pellagra rates were also higher.

One might wonder if these estimates conflate changes in income with changes in food

availability: perhaps years of high cotton production were also years of low income, and

it was the reduction in income, not the reduction in local food production, that drove the

increase in pellagra. Two pieces of evidence, however, suggest this is not the case. First,

the positive correlation between cotton production and pellagra survives the inclusion

of controls for changes in farm revenue generated per acre of cotton. Second, the arrival

of the boll weevil during the early 1900s reduced both income and cotton production,

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and yet was associated with increased food production and reduced pellagra rates.

Moreover, when cotton production rebounded after the boll weevil, pellagra rates

returned to their pre-boll-weevil levels.

After exploring the relationship between cotton production and pellagra, we

search for evidence on the forces behind the decline in pellagra rates during mid-

twentieth century. The raw data reveal two sharp drops in the pellagra death rate. The

first break occurs during the early 1930s, at the peak of the Great Depression. The second

sharp drop in the pellagra death rate is permanent and takes place during the late 1930s

and 1940s. Because this drop happens at around the same time that state and federal

governments introduced laws encouraging and mandating that breads and grains be

enriched with niacin, historical observers have long attributed a causal connection

between the laws and the reduction in pellagra. Using a panel of state-level data and a

standard difference-in-differences set up, we exploit the interstate variation in the timing

of niacin-fortification laws to identify their effects on pellagra and other nutrition-related

diseases. Consistent with the prevailing historical literature, the results suggest

fortification laws significantly reduced the mortality associated with pellagra and low

niacin consumption more generally.

In the final part of our analysis, we look at the long-term effects of early life

exposure to high pellagra (low-niacin consumption) environments. Building on work in

an earlier section of the paper and using a difference-in-differences estimation strategy,

we first study how the arrival of the boll weevil, and the subsequent increase in local

food production, affected the heights (a now common barometer of early-life health and

nutrition) of World-War II army recruits. The results suggest that the arrival of the boll

weevil gave rise to taller, healthier soldiers, despite the reductions in farm income likely

associated with the arrival of the boll weevil. The results are, moreover, most

pronounced in counties producing high levels of cotton and in states with high pre-boll

weevil pellagra rates. Following Neimish (2015), we also explore how early-life exposure

to state-level niacin-fortification laws affected wages in the long-term. We find that

fortification increased wages by approximately 2% amongst Southerners born after a

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state passed a fortification law. The results are, again, larger for states that had higher

levels of pre-fortification pellagra.

Taken together, our results contribute to the following literatures. The first, and

probably the most important contribution, is to our understanding of the economic

history of the American South. The American South has long lagged behind the North in

economic performance, and only after World War II did incomes begin to converge.

Until 1940, income per capita in the South was 45 to 60 percent of the U.S. average; by

1980, that deficit had been reduced to 80 to 95 percent (Wright 1987). Standard

explanations for these patterns fall into one of three categories. Institutional explanations

consider national labor standards (Wright 1987); Civil Rights legislation (Wright 2013,

Collins 2003); and the decline of paternalism and other institutions hostile to black

economic progress (Alston and Ferrie 1993, 1999). Technological explanations focus on

air-conditioning (Biddle 2008, 2012), electrification (Downs 2014), and the mechanization

of agriculture (Alston and Ferrie 1993, 1999). Disease-based explanations consider the

eradication of hookworm and malaria (Bleakley 2007, 2010; Kitchens, 2013). The results

here suggest a fourth possible mechanism: improved nutrition.

Second, there is a large and developing literature exploring how exposure to

poor nutrition and parasitic diseases early in life adversely affect later life outcomes in

terms of income, health, and educational attainment (see, for example, Bleakley 2007,

2010; Rivera et al. (1995); Hoddinott (2008)). To achieve identification, the current

literature often focuses on negative shocks that adversely affect both nutrition and

income (broadly construed). In a recent survey, for example, Lumey et al. (2011) reviews

papers focusing on the Siege of Leningrad of 1941–1944 (Barber and Dzeniskevich 2005);

the Dutch Hunger Winter of 1944–1945 (Trienekens 2000); crop failures in nineteenth-

century Sweden and Finland (Bygren et al. 2000; Kannisto et al. 1997); seasonal famines

in the Gambia between 1949 and 1994 (Moore et al. 1997); the Chinese Great Leap

Forward famine of 1959–1961 (Smil 1999) and recent seasonal famines in Bangladesh

(Moore et al. 2004). The results here complement and extend this literature. Of particular

interest, we believe, are the effects of the boll weevil. What makes the boll weevil shock

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interesting is that it breaks the usual correlation between nutrition and income: most

shocks that reduce nutrition also reduce income, and it is difficult to disentangle the two

effects as they are mutually reinforcing; but the boll weevil forced farmers to abandon a

profitable crop (cotton) for less profitable crops (local food production) and yet historical

observers believed the arrival of the boll weevil promoted better nutrition because of

this shift. The data bear out this hypothesis.

Third, the observation that malnutrition can emerge in poor agricultural societies

that rely heavily on cash crops is not unique to the American South. Describing

conditions in the developing world in the late 1960s and early 1970s, the National

Academy of Sciences (1978, p. 44) explained that “changes in agricultural practices from

mixed cropping to monocroppoing for cash and export . . . [might] result in health

problems ranging from nutrition disorders to increased incidence of parasitic and

infectious diseases.” A recent World Bank study of Malawi linked cash cropping, and

subsequent displacement of local food production, to higher food prices and stunting in

later life (Wood et al. 2013). Similarly, a longstanding critique of British policy in colonial

India is that it fostered an undue reliance on cash crops, which disrupted local food

production and left the indigenous populations poorly fed and vulnerable to frequent

famines (Bhatia 1963).

2. Historical background and preliminary observations

Physicians and public health experts have long characterized pellagra by the four

D’s: dermatitis, diarrhea, dementia, and death. Other symptoms include: sensitivity to

sunlight; aggression; emotional disturbances; edema; inflammation of the tongue; skin

lesions; insomnia; weakness; mental confusion; ataxia (loss of coordination) and

paralysis in the extremities; and enlarged heart. Much like smallpox, which gave rise to

a distinctive rash that made diagnosing severe cases of the disease easy, the dermatitis

and skin discoloration associated with severe cases of pellagra facilitated a proper

diagnosis. That said, for less severe cases, where the pathognomonic features of the

disease were less pronounced, particularly those in relation to the skin, pellagra would

7

have been harder to distinguish from other ailments and may well have been

underreported. These observations have clear implications for our empirical analysis. In

particular, death rates for pellagra are probably well estimated because of the

distinctiveness of the disease in severe cases, but incidence rates likely understate the

prevalence of the disease.

Today the causes of pellagra are well understood. As noted above, the primary

cause of the disease is inadequate niacin consumption, and secondary causes include a

deficiency in tryptophan (which is found in meat, fish, and eggs, and the body converts

to niacin) and excess leucine (which inhibits niacin metabolism). Historically, however,

the causes of pellagra were poorly understood. During the early 1900s, Southerners

steadfastly rejected any claim that the disease might be associated with poverty and

poor diets. They saw such claims an indictment of Southern culture and habits, and

instead argued that pellagra was spread by flies or spoiled corn (Mooney et al. 2014).

The first person to begin effectively arguing that pellagra was a nutritional disease was

Joseph Goldberger, who worked for the United States Public Health Service in the late

1910s and early 1920s. Through a series of detailed studies of diets in orphanages,

sanitariums, and mill towns, Goldberger and his colleagues documented a tight

correlation between diet and pellagra (Goldberger et al. 1915, 1920, 1929). But it was not

until 1937 that Conrad Elvehjem showed definitively that pellagra was caused by

inadequate niacin consumption (Elvehjem et al. 1937).

The first reported case of pellagra in the United States occurred in Georgia in

1902 and reached broader proliferation around 1906 (Bollet 1992). Historical observers

have attributed the emergence of pellagra to changes in the milling of Midwestern corn.

Previous milling technology had removed less of the germ, retaining some niacin.

Newer technology removed the germ more completely, leading to a finer corn meal with

a longer shelf life but much less niacin and other micronutrients. Expansion of large-

scale milling and movements of goods by railroad meant that this corn reached the

South in increasing quantities. Bollet (1992, p. 219) notes that “in the textile mill towns,

surrounded by cotton fields, food was shipped in by railroad, and the cornmeal that

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could be purchased in the company stores was processed in the Midwest, where it had

been degerminated.” In addition, a report from the Thompson-McFadden Pellagra

Commission found that in six mill towns in South Carolina 2,515 residents (49%)

consumed shipped cornmeal daily, 1,563 residents (30%) consumed shipped cornmeal

habitually, and 1,052 residents (21%) consumed ship cornmeal rarely. This in contrast to

the consumption of locally grown corn. They found that 628 residents (12%) consumed

local corn daily, 291 residents (6%) consumed local corn habitually, 120 residents (2%)

consumed local corn rarely, and 4,050 residents (80%) never consumed local corn (Siler

et al. 1914).

Figure 1 maps the regional variation in pellagra rates and shows that this change

in corn milling and the subsequent emergence of pellagra hit the South particularly hard.

While there was some pellagra in the border states and the Southwest, the disease

reached its peak in the deep South, particularly, Alabama, the Carolinas, Florida,

Georgia, Louisiana, Mississippi, and Tennessee.

Why did the change in corn milling hit the South so hard? Aside from salt pork

and molasses (neither of which was particularly high in niacin), the Southern diet was

based mostly on corn. Niacin rich foods, such as fish, lamb, and poultry, were expensive

and were not regularly consumed by poor Southern households (Hilliard 1969). Table 1

documents the Southern proclivity to eat corn. This table is based on The Study of

Consumer Purchases in the United States, 1935-1936, which collected data on food

purchases from a large sample of households including Southern residents, Southern

rural residents, and non-Southern residents. The table shows that while rural dwellers in

the South ate less white bread than non-Southerners, they consumed far more corn meal

and hominy grits (which are made from corn). In particular, Southern rural residents

consumed 4.25 pounds of corn meal and hominy and 1.13 pounds of white bread per

week. Non-Southern residents consumed 0.09 pounds of corn meal and hominy and 4.33

pounds of white bread per week. These differences are all highly significant.

The introduction of degerminated Midwestern corn probably would not have

mattered as much had Southerners produced more corn for local consumption. Corn

9

that was grown and marketed for local consumption would have been consumed

relatively quickly and the incentives to preserve it through milling and degermination

would have been less pronounced. Locally-sourced corn could also be used to make

hominy grits; milled corn from the Midwest could not. If prepared correctly, hominy

grits would have contained more niacin than ordinary corn, corn meal, or corn bread.

Along these lines, while corn-based diets are generally correlated with pellagra, many

Indian societies with corn-based diets have managed to avoid pellagra because of their

heavy reliance on hominy grits which involved soaking the corn in a lime/alkali solution

that catalyzed the grain’s potential niacin and tryptophan (Carpenter 1983). In addition,

Southerners tended to plant and harvest sweet corn, which contained relatively high

levels of niacin, while the corn varieties grown in the Midwest contained 30 to 50

percent less niacin than sweet corn (Burkholder et al. 1944; Ayer 1895, p. 12-13). The

upshot of all this is that as long as Southerners were consuming fresh, locally-grown

corn that was not milled they would have been consuming more niacin than they did

with imported Midwestern corn.

One of the central themes of the extent literature on pellagra is that the disease

stemmed directly from the South’s cotton monoculture. In his study of South Carolina,

Edgar (1992) argues that a high debt burden forced many farmers to plant cotton, a cash

crop with higher expected returns than other crops such as foods for the local market. In

1910, one of every five cultivated acres was devoted to cotton; by 1919 one of every two

cultivated acres was devoted to cotton. Furthermore, despite the population of South

Carolina tripling from 1850 to 1935, the amount of food production remained about the

same. As a result, South Carolina “had to import $70-$100 million worth of food

annually. For poverty-stricken tenant farmers with little ready cash, this meant that

there was less to eat. The consequent increased dependence on a diet of pork, cornbread,

and molasses made poor Carolinians more susceptible to disease” (Edgar 1992, pg. 47).

A more general way to state this argument is the following: the production of

cotton displaced local food production, and prompted poor Southern cotton farmers and

laborers to import and consume corn from the Midwest, which though cheap, was also

10

degerminated and devoid of niacin. (See Lange et al. (2009) for evidence that cotton

displaced corn production.) If so, one would expect a strong positive correlation with

cotton production and pellagra. In years when cotton production was high (and

crowded out the harvesting of food for local markets) pellagra rates should have risen,

while in years of low cotton production (and by implication, relatively high rates of local

food production) pellagra rates should have fallen.

Looking at trends in pellagra and cotton production, the data are broadly

consistent with this view. Panel A of Figure 2 plots two time-series: the pellagra death

rate in the American South from 1910 to 1950 and cotton-acres harvested from 1880 to

1950. These data suggest that pellagra erupted in the American South after two decades

of steady growth in the amount of Southern farmland dedicated to cotton production.

The explosive growth in pellagra stops during the late 1910s at around the same time

that the cotton economy stagnates with the penetration of the boll weevil. Pellagra

rebounds during the late 1920s, shortly after the effects of the boll weevil begin to recede

and the cotton economy recovers. Pellagra plummets again during the late 1920s and

early 1930s, with the onset of the Great Depression and a sharp decline in cotton-acres

harvested. It is only after the discovery of niacin in 1937, marked by the horizontal line

in the graph, and the passage of laws mandating the fortification of grains and breads

with niacin, that the correlation between cotton production and pellagra seems to break

down. Panel B, C, and D of Figure 2 plot similar graphs for North Carolina, South

Carolina, and Louisiana. North Carolina and South Carolina will be particularly

important for our analysis since they are the only states that report pellagra deaths at the

county level during this time period.

Plotting pellagra directly against annual cotton acres harvested, Figure 3

highlights the correlation between pellagra and cotton production more clearly. What

remains unclear, however, is the extent to which one might attribute causality to this

relationship. One obvious concern is the large number of potentially confounding events

during the 1900-50 period. In particular, there is a well-developed literature

documenting the long-term economic significance of the events like the Great Influenza

11

Pandemic (Almond 2006; Clay, Lewis and Severnini 2015; and Noymer 2010); iron

enrichment (Neimish 2015); the Great Migration (Black et al. 2015); various New Deal

programs, particularly those aimed at agriculture (Depew et al. 2013); the eradication of

malaria and hookworm (Bleakely 2010, 2007); milk fortification; and salt iodization

(Adhvaryu et al. 2015, Feyrer et al. 2013). Any of these events might confound the time

series above and/or interact with pellagra in important ways.

In the empirical analysis that follows we, therefore, take steps to control for these

and other potential confounders. We believe that many of the confounders will be

differenced out with year and state/county fixed effects. We will also control for the

malaria death rate and a measure of cash crop revenue in some specifications. Finally,

for interventions like milk fortification, migration, and salt iodization to drive our results

they would have to work through very specific channels. For instance, for migration to

be driving our results it must be the case that only unhealthy individuals migrate out of

a location. Similar stories would need to be told for milk fortification and salt iodization,

whereby adding iodine to salt somehow leads people to consume more niacin.

Building on an older literature, one might also argue that the South was over-

producing cotton, and that as a result, years of high cotton production were also years of

low income.3 In this case, pellagra would not have been the result of cotton displacing

local food production (and raising the price of such food); instead, the disease would

have stemmed from the fact that cotton production was driving down income and the

reduction in income, not the displacement of local food, caused families in the cotton

South to consume less food.

3. A Simple Economic Framework

In this section, we sketch out a simple economic framework that can explain

how the South’s reliance on cotton might have promoted higher pellagra rates in

particular, and poor nutrition more generally construed. One of the central messages of

3 See McGuire and Higgs (1978) and McGuire (1980) for evidence on the profitability of cotton.

12

this framework is that cash cropping does not necessarily result in poor nutrition; it only

does so under certain conditions.

Consider, then, a largely agricultural economy, where farmers are deciding how

to allocate their land, labor, and capital: they can either plant, harvest, and sell a cash

crop in an international market, in this case, cotton; or they can deploy their resources to

produce food for the local market. In deciding how to allocate resources, farmers look

toward expected prices. To the extent expected cotton prices are relatively high, farmers

would allocate their land and resources to planting and selling cotton and produce little,

if any, food for the local market. Driving up the relative price of locally-produced foods,

consumers in this economy would substitute away from such foods and begin importing

degerminated corn from the Midwest, which as noted above, was niacin deficient. As an

empirical matter, we cannot observe the expected price of cotton or the price of locally

produced foods, and instead rely on acres dedicated to cotton and food production,

which will usually be highly correlated with expected prices. However, we will also

discuss and exploit situations were expected prices do not drive planting decisions.

For the process above to have yielded high rates of pellagra, two conditions need

to be satisfied. First, it must be the case that there are, in fact, nutritional differences

between imported corn and locally-sourced foods. While we cannot directly test this

proposition, there is anecdotal evidence to suggest this was the case. In the case of corn,

locally-produced corn did not require degermination to extend shelf life and so it is

thought to have been healthier and richer in niacin. There is also evidence (discussed

below) that aside from corn, Southern farmers would switch to growing peanuts when

cotton prices were low or when cotton production was not feasible. Peanuts were rich in

niacin and other micronutrients. Second, it must the case that the price effect dominates

any income effect. More precisely, if demand for nutrition grows with income and

higher cotton prices, it is possible that consumers in the region might begin importing

relatively expensive niacin-rich foods, rather than degerminated corn. Put another way,

if cash cropping generates sufficiently high wages and income and nutrition is a normal

good, cash cropping need not imply poor nutrition.

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4. Data and empirical strategy

4.a. Data

County and individual level data from several sources are used to document the

rise and fall of pellagra in the American South. Consistent data on pellagra deaths at the

county level during our study period are, to our knowledge, only available for North

Carolina and South Carolina. Pellagra deaths for counties in North Carolina from 1915-

1950 come from The Annual Report of the Bureau of Vital Statistics of the North Carolina State

Board of Health.4 We have also collected county-level death counts for malaria, measles,

typhoid, and tuberculosis from 1915-1930. We use these diseases as placebo tests in our

analysis. The North Carolina State Board of Health did not issue a Vital Statistics report

for the years 1918 and 1919 so we do not have data on deaths for these years. Pellagra

deaths for county in South Carolina from 1915-1925 come from Annual Report of the State

Board of Health of South Carolina.5 To calculate the pellagra death rate at the county-level

every year we perform a linear interpolation of the county population in-between

censuses.

Data on crop acreage at the county-level comes from Haines et al. (2015) United

States Agriculture Data, 1840-2010. These data are a digitized version of data originally

provided in publications from the United States Bureau of the Census. These data

provide county-level crop production for years in which the Census of Agriculture was

performed. Specifically, we use data on cotton, corn, peanut, and sweet potato acreage.

To calculate acreage per capita in every year we linearly interpolate both the county

population and crop acreage.

To study the long-run effects of nutrition we first look at the height of World

War II recruits. Heights of World War II recruits come from the World War II Army

Enlistment Records 1938-1946 provided by the National Archives and Records

4 In 1920 and 1921 these reports are found in The Health Bulletin published by the North Carolina

State Board of Health. 5 We are in the process of digitizing the remainder of the South Carolina death data, which

should eventually give us a time-series to 1950.

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Administration. These micro-level data provide height for approximately 9.2 million

World War II soldiers. We make several sample restrictions to obtain a sample that is

likely to be representative for each cohort. We restrict to white men who were drafted,

born in the South, born between 1915 and 1921, enlisted between 1940 and 1946, report a

valid height (between 5 feet and 6.5 feet), and report a valid weight (between 100

pounds and 400 pounds).6 Since we do not observe county of birth, we further restrict to

soldiers that were living in the same state they were born in at the time of enlistment.

For these soldiers we assume that at the time of enlistment they were living in the same

county they were born in.

Finally, we look at the long-run effects of fortification laws on income using the

1% Integrated Public Use Micro Sample (IPUMS) for the United States Census in 1970, 1980,

and 1990 (Ruggles et al. 2015). We restrict to individuals who are born in the United

States, since individuals born outside the United States might not have been exposed to

fortification during childhood. We further restrict to individuals born 4-6 years prior to

the passage of a mandatory fortification law and individuals born 1-3 years after the

passage of a law. As discussed in section 7.b., most of the effect of nutrition on later life

outcomes occurs during the first three years of life. By restricting to individuals born 4-6

years prior to the passage of a law we are removing individuals who might have been

partially exposed to improved nutrition during early life. We, therefore, compare

individuals who are not exposed to improved nutrition during childhood to those born

just after the passage of a law and, therefore, completely exposed to improved nutrition

during early childhood.

4.b. Empirical Strategy

We estimate the effect of the boll weevil, voluntary fortification, mandatory

fortification, and long-run outcomes using a standard difference-in-differences intensity

of treatment model. Our baseline model is given by:

6 We define Southern states to include: Alabama, Arkansas, Florida, Georgia, Louisiana,

Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, and Virginia.

15

[𝑜𝑢𝑡𝑐𝑜𝑚𝑒]𝑐𝑡 = 𝛼 + 𝜃1 ∗ [𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 + 𝜃2 ∗ [𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 × [𝑖𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦]𝑐 + 𝜃𝑐

+ 𝜃𝑡 + 𝜀𝑐𝑡

(1)

In equation (1), [𝑜𝑢𝑡𝑐𝑜𝑚𝑒]𝑐𝑡 is our outcome of interest (usually the log of the pellagra

death rate) in county c in year t. When using height and the log of income as the

outcome the variable is recorded at the individual level not at the county level. When

analyzing the boll weevil, [𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 is an indicator variable that takes a value of one

after the boll weevil has arrived in a county. When analyzing voluntary fortification,

[𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 takes a value of one starting in 1937. When analyzing mandatory

fortification, [𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 takes a value of one starting in the year a state passed a

mandatory fortification law. We interact [𝑡𝑟𝑒𝑎𝑡𝑚𝑒𝑛𝑡]𝑐𝑡 with a county level measure of

the intensity of the treatment: [𝑖𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦]𝑐. The intensity of treatment variables will be

explained as they are introduced. All intensity of treatment variables have been

normalized so they have a mean of zero and a standard deviation of one. Finally, we

include county fixed effects to control for unobserved time invariant county

characteristics and year fixed effects to control for any unobserved shocks in a particular

year. The standalone term, [𝑖𝑛𝑡𝑒𝑛𝑠𝑖𝑡𝑦]𝑐 , is completely absorbed by the county fixed

effects. Standard errors are clustered at the county-level.

As mentioned in Section 2 there are a number of factors that might confound our

analysis. We believe that most of these factors will be differenced out as a result of our

difference-in-differences analysis. For example, if the Great Influenza Pandemic of 1918

interacts with pellagra in some way, than this should only be true in the year 1918 and

will be differenced out in our year fixed effects. According to Bleakley (2010) the malaria

intervention in the American South occurs almost concurrently with the arrival of the

boll weevil in North and South Carolina. Again, the malaria intervention might interact

the pellagra and confound our results. Accordingly, we control for the malaria death

rate in certain specifications. Finally, a valid potential confounder of our boll weevil

analysis would involve migration out of counties that were hit by the boll weevil. We

16

discuss the type of selection that would be required for migration to drive our results in

section 5.b.

5. Cotton and the rise of pellagra

5.a. Relationship between cotton and pellagra

Although the existing literature on pellagra posits a causal relationship between

cotton production and pellagra, there is a dearth of systematic data establishing even a

correlation between the two. Accordingly, in this section, we analyze state and county-

level data for evidence of a correlation between cotton production and pellagra. The

state-level analysis provides the advantage of having annual data for both pellagra

death rates and crop acres harvested. The county-level analysis provides the advantage

of a much finer geographic unit despite only being able to measure crop acreage when

the Census of Agriculture is taken. We also search for evidence that cotton production

displaced the production of local foods, particularly corn, peanuts, and sweet potatoes.

We begin our empirical analysis by exploring the relationship between land

devoted to cotton production and pellagra, as previously demonstrated in Figures 2 and

3. To examine this relationship we first collect data on the number of pellagra deaths in a

state from the Mortality Statistics of the United States starting in 1900. We combine these

data with state-level data on the number of acres of cotton, corn, peanuts, and sweet

potatoes harvested yearly and the number of 480-pound cotton bales that were

produced.7 We restrict our attention to only the nineteen states that produced cotton

over this period and we note that we do not have a balanced panel. States enter our

sample as they begin reporting to the Mortality Statistics of the United States. The first

cotton producing states to report to the Mortality Statistics are California and North

Carolina in 1910. Furthermore, we believe that the relationship between cotton, corn,

peanut, and sweet potato acreage and pellagra should be most pronounced prior to the

7 These data come from the United States Department of Agriculture, National Agricultural

Statistics Service Database.

17

discovery of niacin and the commencement of fortification in 1937. For these two reasons,

we restrict our attention to the period 1910-1936. We estimate the following equation:

𝑙𝑛[𝑝𝑒𝑙𝑙𝑎𝑔𝑟𝑎]𝑠𝑡 = 𝛼 + 𝜃1 ∗ [𝑐𝑟𝑜𝑝 𝑎𝑐𝑟𝑒𝑠 𝑝𝑐]𝑠𝑡 + 𝜃2 ∗ [𝑐𝑜𝑡𝑡𝑜𝑛 𝑟𝑒𝑣𝑒𝑛𝑢𝑒]𝑠𝑡 + 𝜃𝑠 + 𝜃𝑡

+ 𝜀𝑠𝑡

(2)

Where ln[pellagra]st is the pellagra death rate in state s in year t. The variable [crop

acreage]st is the number of acres per capita of a given crop. The variable [cotton revenue]st

is the revenue per acre of cotton harvested.8 State and year fixed effects are included in

the model. All crop acreage per capita variables are normalized to have a mean of zero

and a standard deviation of one. Standard errors are clustered at the state-level.

The results from estimating equation (2) are given in Table 2. In column (1), a one

standard deviation increase in cotton acres per capita is associated with an increase in

the pellagra death rate by approximately 6%. Columns (2)-(4) show that when states use

their land to produce local, nutritional food, the pellagra death rate is lower. A one

standard deviation increase in acres per capita devoted to corn, peanuts, or sweet

potatoes significantly decreases the pellagra death rate by 1.4-4%.

Using the same data we show evidence that, because land is fixed, food

production will likely decrease when acres devoted to cotton production increases. To

show this relationship we estimate the following equation:

[𝑓𝑜𝑜𝑑 𝑎𝑐𝑟𝑒𝑠 𝑝𝑐]𝑠𝑡 = 𝛼 + 𝜃 ∗ [𝑐𝑜𝑡𝑡𝑜𝑛 𝑎𝑐𝑟𝑒𝑠 𝑝𝑐]𝑠𝑡 + 𝜃𝑠 + 𝜃𝑡 + 𝜀𝑠𝑡 (3)

where [food acres pc]st is the number of acres per capita devoted to the production of corn,

peanuts, or sweet potatoes and [cotton acres pc]st is the number of acres per capita

devoted to the production of cotton. Again, all crop acreage per capita variables are

8 National cotton prices come from the Historical Statistics of the United States Database; series

Da755-765.

18

normalized to have a mean of zero and a standard deviation of one. We now begin our

analysis in 1900 since, unlike pellagra, crop acreage is reported back to 1900.

Table 3 provides the results from estimating equation (3). Column (1) shows that

increasing cotton acres per capita by one standard deviation decreases corn acres per

capita by 0.58 standard deviations. In column (2), a one standard deviation increase in

cotton acres per capita is associated with a decrease in peanut acres per capita by over

one standard deviation. Finally, in column (3), a one standard deviation increase in

cotton acres per capita is associated with a decrease in sweet potato acres per capita by

approximately 0.13 standard deviations.

We further test relationships between crop acreage and pellagra at the county-

level. The county-level relationship between pellagra and crop acreage is shown in

columns (5)-(8) of Table 2. Column (5) shows that a one standard deviation increase in

cotton acres per capita is associated with an increase in the pellagra death rate by

approximately 19%. In column (6), a one standard deviation increase in corn acres per

capita is associated with a decrease in the pellagra death rate by approximately 16%.

Finally, the coefficients in columns (7) and (8), which report the relationship between

pellagra, peanuts, and sweet potatoes, are both small and insignificant.

Finally, we show evidence that cotton production displaces food production at

the county-level in Table 3. In column (4), a one standard deviation increase cotton acres

per capita is associated with a decrease in corn acres per capita by approximately 0.32

standard deviations. The coefficients in columns (5) and (6), which show the relationship

between cotton, peanut, and sweet potatoes, are once again small and insignificant.

Tables 2 and 3 provide evidence about one of the primary causes of the rise of

pellagra in the United States. Table 2 demonstrates that, in the pre-fortification period,

the pellagra death rate increased when land devoted to cotton production increased, and

decreased when the land devoted to cotton production decreases. Table 3 demonstrates

that a likely reason for this relationship is the crowding-out of local food production by

cotton. Since land is fixed, if farmers decide to dedicate more land to cotton production

they, necessarily, must dedicate less land to the production of locally grown foods. The

19

decline in local food production means that individuals must consume more imported

food that was, usually, lower in nutritional value. These results hold at both the state

and the county level.

Despite the consistent results in Tables 2 and 3, there is still the potential concern

that high cotton production is associated with unobserved factors that increase the

pellagra death rate. For example, perhaps cotton production decreases income, which

leads to worse diets and increases in pellagra. To deal with these concerns, we next turn

our attention to an exogenous shock to cotton production that was brought about by the

arrival of the boll weevil.

5.b. The Boll Weevil

The boll weevil, a beetle that feeds on cotton leaves, squares (flower buds), and

bolls, appeared in Texas in 1892. Figure 4 shows its progression through the cotton belt.

By 1922, the boll weevil had infected the entire cotton region. The arrival of the weevil

has significant impacts on agriculture. Lange et al. (2009) show that the arrival of the boll

weevil reduced county cotton production, yields, and land values. They also find

evidence that farmers shifted crops after the arrival of the boll weevil (p. 710): “The

decline in cotton acreage raises the question of what southern farmers did with the

released land. … Overall, the corn results indicate a greater movement to alternative

crops than suggested in the literature, which has downplayed the boll weevil’s effects on

diversification.” They also write in a footnote that (p. 710): “Based on the census data,

we also find production of hay, Irish potatoes, peanuts, rice, and sweet potatoes; sugar

cane, among other crops, showed statistically significant increases after the arrival of the

weevil.”

The invasion of the boll weevil allows us to exploit an exogenous change in crop

mix that arguably affected health. Data on the year the boll weevil first arrived in a

county are taken from Lange et al. (2009), which originally came from USDA boll weevil

maps. To examine the impact of the boll weevil on pellagra we estimate equation (1). We

use two different variables to measure intensity of treatment. Our first variable is the

average pellagra death rate in 1915 and 1916, just before the boll weevil arrived in North

20

Carolina and South Carolina. The idea is that places with higher pre-boll weevil pellagra

death rates likely had worse baseline nutrition and, therefore, had more to gain from the

arrival of the boll weevil. Our second intensity of treatment variable is cotton acres per

capita in the county in 1909, which is the year closest to the arrival of the boll weevil that

the Census of Agriculture was taken in.

Table 4 shows the impact the boll weevil had on pellagra death rates in the North

Carolina and South Carolina. Column (1) indicates that the pellagra death rate decreased

by 25% after the arrival of the boll weevil in a county. Column (2) indicates that for the

county with the average amount of pellagra prior to the arrival of the boll weevil, the

pellagra death rate decreased by 25%. However, a one standard deviation increase in the

pre-boll weevil pellagra death rate is associated with an additional decrease in the

pellagra death rate of approximately 29%. In column (3), we show that for the county

with the average amount of cotton acres per capita prior to the arrival of the boll weevil,

the pellagra death rate decreased by 25% after the arrival of the boll weevil. A one

standard deviation increase in cotton acres per capita is associated with an additional 4%

decrease in the pellagra death rate. Finally, in column (4) we restrict to only counties that

produced over 100 acres of cotton in 1889.9 We, again, find that the arrival of the boll

weevil is associated with a 19% reduction in the pellagra death rate.

Columns (1)-(4) are estimated over the time period 1915-1950 and, as discussed

in the introduction, there were several other events that lowered the pellagra death rate

over this time period; specifically the Great Depression and fortification laws. In column

(5) we restrict the period of our study to 1915-1929; before the start of the Great

Depression and the passage of fortification laws. We also control for the county-level

malaria death rate in each year since the effort to reduce malaria in the American South

occurred almost concurrently with the arrival of the boll weevil in North Carolina and

South Carolina. We, again, find that the arrival of the boll weevil in a county is

associated with a decrease in the pellagra death rate by approximately 20%. Finally, for

9 As shown in Figure 4, cotton cannot be grown in several counties in the western part of North

Carolina.

21

our story to be consistent the arrival of the boll weevil should not be associated with

significant decreases in non-nutrition related diseases. In column (6) we examine

typhoid, in column (7) we examine tuberculosis, and in column (8) we examine measles.

The coefficient for the arrival of the boll weevil for all three diseases and is positive and

not significant. Thus, the arrival of the boll weevil was not associated with general

improvements in health, but instead it was only associated with improvements in

nutrition. After all, the only way to cure pellagra is to consume more niacin.

As already mentioned, a potentially valid confounder of our boll weevil analysis

involves migration out of counties that were hit by the boll weevil. Indeed, Lange et al.

(2009, p. 715) find “the weevil appears to have unleashed a wave of internal migration,

leading to local population gains before contact and substantial losses after the onset of

significant crop damage.” The placebo tests in Table 4, columns (6)-(8), show that the

least healthy members of the population are not selectively leaving a county after the

arrival of the boll weevil. Therefore, for selective migration to be driving our results it

must be the case that only individuals who are so poorly nourished that they develop

pellagra migrate out of the county, while other unhealthy individuals do not.

6. Niacin and the fall of pellagra

6.a. Voluntary Fortification

Shortly after 1937, when niacin was identified as the cause of pellagra, voluntary

fortification of cereal-grain products began (Park et al. 2000, 2001). In 1939, the Council

on Foods and Nutrition of the American Medical Association encouraged “with some

qualification, fortification of certain staple foods with vitamins and minerals, specifically

the restorative additions of thiamine, niacin, riboflavin, iron, and calcium to white flour

and white bread” (Wilder 1956, pg. 1540). In 1941 the FDA established standards for the

fortification of bread, which are displayed in Table 5. Up to January of 1943, fortification

was increasingly common, but remained voluntary. Further, it was primarily restricted

to bread and flour. Fortification was briefly required at the national level, due to War

22

Food Order No. 1. When federal war powers ended, regulation devolved to the states, at

which point, several states passed mandatory fortification laws.

Table 6 provides estimates of equation (1) and shows the effect of voluntary

fortification on the pellagra death rate. As mentioned in section 4.b., The variable

[treatment]ct takes a value of one beginning in 1937. For the state-level analysis the

intensity of treatment variables are the pre-niacin pellagra death rate and pre-niacin

cotton acres per capita; both variables are averages over the years 1932-1936. In the

county-level analysis we measure pre-niacin cotton acres per capita as the average from

the years 1929 and 1934. Finally, since our treatment variable turns on in 1937 we do not

include year effects, but instead, include a quadratic time trend.

Columns (1)-(3) examine the state level impact of voluntary fortification. In

column (1), voluntary fortification is associated with a decrease in the pellagra death rate

by 2%. In column (2) we show that virtually the entire decrease in the pellagra death rate

is located in states with high pre-niacin pellagra death rates; a one standard deviation

increase in the pre-niacin pellagra death rate is associated with a decrease in the pellagra

death rate of 6%. Finally, a one standard deviation increase in pre-niacin cotton acres per

capita is associated with a 4.5% decrease in the pellagra death rate.

Columns (4)-(6) examine the county level impact of voluntary fortification in NC.

In North Carolina, voluntary fortification is associated with an 18% decrease in the

pellagra death rate (column (4)). Column (5) shows that a one standard deviation

increase in the pre-niacin pellagra death rate is associated with a decrease in the pellagra

death rate of 25%. Finally, column (6) shows that a one standard deviation increase in

pre-niacin cotton acres per capita is associated with a 6% decrease in the pellagra death

rate [p-value = 0.109]. Table 6 provides strong evidence that the voluntary fortification of

cereal-grain products, beginning in 1937, was associated with significant decreases in the

pellagra death rate.

6.b. Mandatory Fortification Laws

23

Pellagra was virtually eliminated in the United States by the passage of

fortification laws that mandated that cereal grain products be enriched with niacin and

other B vitamins, as well as iron. Twenty-eight states passed some form of a mandatory

fortification law over the decade 1940-1949. Figure 1 shows the states and years in which

fortification laws were passed. The year of fortification law passage was taken from Park

et al. (2001). Most of these laws required bread and flour to be enriched with thiamine,

niacin, riboflavin, iron, and calcium, however, many laws in Southern states also

pertained to cornmeal and hominy grits, as these were staples of the Southern diet.10 As

a result, major producers of corn meal and grits in the Midwest began fortifying their

products. A 1957 survey found that nearly all hominy grits sold were enriched, and that

cornmeal was generally enriched, except in Florida and Virginia, where enrichment was

less typical (Park 2001, NRC 1958).

We again, estimate equation (1) using the intensity of treatment measures as they

were defined in section 6.a. The variable [treatment]ct takes a value of one beginning in

the year that a mandatory fortification law was passed by a state. We once again include

state fixed effects in the state-level analysis since there is variation in the years that states

passed enrichment laws. In the county-level analysis the quadratic time trend is used

since we only have data for North Carolina.

Table 7 shows the effect of mandatory fortification laws on the pellagra death

rate. Columns (1)-(3) examine the state-level impact. The passage of a fortification law is

associated with a decrease in the pellagra death rate by approximately 6% (column (1)).

In column (2), we show that a one standard deviation increase in the pre-niacin pellagra

death rate is associated with a decrease in the pellagra death rate by 5%. In column (3), a

one standard deviation increase in the pre-niacin number of cotton acres per capita is

associated with a 2% decrease in the pellagra death rate.

Columns (4)-(6) examine the county-level impact of the North Carolina

mandatory fortification law, which was passed in 1945. The passage of the mandatory

10 States that passed laws pertaining to corn meal and hominy grits were: Alabama, Georgia,

Mississippi, North Carolina, South Carolina, and Texas.

24

fortification law is actually associated with a 13% increase in the pellagra death rate in

NC (column (4)). Note however, that if the quadratic time trend is not included in the

model, the passage of the mandatory fortification law is associated with a 5% reduction

in the pellagra death rate. This indicates that our regression analysis has difficulties

separating the effects of the law passage from the pre-existing trend, which is potentially

the result of voluntary fortification.

In column (5), a one standard deviation increase in the pre-niacin pellagra death

rate is associated with a decrease in the pellagra death rate by 19%. Finally, a one

standard deviation increase in the pre-niacin amount of cotton acres per capita is

associated with a 5% decrease in the pellagra death rate. Table 7 demonstrates that the

passage of mandatory fortification laws were associated with significant decreases in the

pellagra death rate. The passages of mandatory fortification laws were also associated

with the virtual elimination of pellagra in the American South by 1950 as shown in

Figure 2.

7. Long-run effects of nutrition

Finally, we turn to the examination of the long-run effects of nutrition. We

believe that the long-run effects of nutrition during early childhood might be

considerable given previous studies. The most important of these studies took place

between 1969 and 1977 in four rural villages in Guatemala. Two villages were randomly

selected to receive a high-energy, high-protein nutrition supplement (atole) and two

villages were selected to receive a low-energy, no-protein nutrition supplement (fresco).

Supplements were provided freely to pregnant and lactating mothers and children

under the age of seven. Schroeder et al. (1995) find that children receiving the nutritious

supplement were taller and weighed more during the first three years of life. Rivera et al.

(1995) find that children receiving the nutritious supplement were taller and weighed

more during adolescence. Finally, Hoddinott et al. (2008) find that exposure to the

nutritious supplement during the first three years of life significantly increased wages

25

by approximately 46%.11 Virtually all studies of the long-run impacts of nutrition find

that nutrition matters most during the first three years of life. As a result of these

findings, we focus on the effects of early childhood nutrition on height and income.

We examine the long-run impact of the improvement in nutrition brought about

by the arrival of the boll weevil on the height of World War II recruits. Using these data

we estimate a model very similar to equation (1), but with individual, rather than state

or county-level data. We include county of birth, year of birth, and year of enlistment

fixed effects in our model.

The results from estimating the model are shown in Table 8. In column (1), the

arrival of the boll weevil is associated with an increase in the height of World War II

recruits by over a tenth of an inch (0.13; p-value 0.107). Column (2) shows that people

born in states with average pre-boll weevil pellagra death rates experienced an increase

in height of about 0.1 inches after the arrival of the boll weevil. A one standard deviation

increase in pre-boll weevil pellagra levels is associated with an additional 0.21-inch

increase in height. Finally, column (3) shows that for recruits born in counties with

average pre-boll cotton acres per capita the arrival of the boll weevil is associated with

an increase in height of about 0.02 inches. A one standard deviation increase in pre-boll

weevil cotton acres per capita is associated with an additional 0.18-inch increase in

height. Table 8 provides strong evidence that the nutritional improvement associated

with the arrival of the boll weevil increased heights for World War II recruits.

Finally, we turn to the long-run impact of mandatory fortification laws on

income. We, again, estimate a model very similar to equation (1), and all intensity of

treatment variables are defined analogously to section 6.a.

Table 9 shows the long-run impact of mandatory fortification laws on income.

Column (1) indicates that individuals born after the passage of a mandatory fortification

law earn approximately 3% higher incomes (p-value = 0.169). In column (2) we see that a

one standard deviation increase from the average pre-niacin pellagra death rate is

11 Yet another study, Haas et al. (1995) finds that consuming the nutritious supplement during the

first three years of life increased physical work capacity (VO2max).

26

associated with a significant 2.5% increase in income. Finally, in column (3) a one

standard deviation increase from the pre-niacin cotton acres per capita is associated with

a 1% increase in income (p-value = 0.105). Table 9 provides convincing evidence that

incomes increase as a result of state-level fortification laws.

8. Conclusion

In this paper we have documented the rise and fall of pellagra in the United

States. The rise of pellagra was associated with increases in cotton production in the

American South and the substitution of locally grown corn for corn that was milled in

the Midwest. The Midwestern milled corn was degerminated, which stripped the corn

of much of its nutritional value. We show strong empirical evidence that pellagra is

positively associated with land devoted to cotton production and that cotton did, indeed,

crowd-out the production of local corn and other crops such as peanuts and sweet

potatoes.

To establish the causal relationship between cotton acreage and pellagra more

definitively we exploit an exogenous shock in cotton production that occurred from the

arrival of the boll weevil. Farmers diversified crops after the arrival of the boll weevil,

which led to improved nutrition and reductions in the pellagra death rate. Furthermore,

we provide evidence that the arrival of the boll weevil was not associated with overall

improvements in health. The death rates for typhoid, tuberculosis, and measles

experience no significant changes after the arrival of the boll weevil. This implies that

the boll weevil’s only short-run impact on health was through improved nutrition.

The fall of pellagra in the American South was associated with the discovery of

niacin as anti-pellagrant in 1937. Shortly after this discovery, bakeries and mills began to

voluntarily fortify their products with thiamine, niacin, riboflavin, iron, and calcium.

Pellagra was virtually eliminated in the United States with the passage of state-level

mandatory cereal-grain fortification laws from 1940-1949. We show that both voluntary

and mandatory fortification significantly decreased the pellagra death rate and led to

pellagra’s elimination around 1950.

27

Finally, we demonstrate that the improvements in nutrition brought about by the

arrival of the boll weevil resulted in significant increases in the height of World War II

recruits. We also show that the improvements in nutrition brought about by mandatory

fortification resulted in significant increase in income for individuals later in life. These

results are consistent with the fact that nutrition in early life leads to permanent, long-

run effects on health and economic performance.

28

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Figures

Figure 1: Distribution of pellagra (1930) and year of fortification law passage

35

Figure 2: Pellagra and cotton acreage in the South and three southern states

Figure 3: Relationship between cotton acres and pellagra in the American South

36

Figure 4: The progression of the boll weevil

Source: Hunter and Coad (1922) The Boll weevil Problem

G enerated for Schm ick, Ethan Jam es (U niversity of Pittsburgh) on 2015-04-21 20:41 G M T / http://hdl.handle.net/2027/uiug.30112019281614

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37

Tables

Table 1: Southern Diets 1935 - 1936

All Southern

residents

Southern

rural

residents

Non-

Southern

residents

Difference

between

columns (2)

and (3)

p-value of

difference

(1) (2) (3) (4) (5)

Pounds of corn meal used in past

week 2.81 3.67 0.07 3.6 0.00***

Pounds of hominy grits used in

past week 0.62 0.59 0.02 0.57 0.00***

Pounds of corn meal and hominy

grits used in past week 3.43 4.25 0.09 4.16 0.00***

Pounds of white bread used in past

week 2.31 1.13 4.33 -3.2 0.00***

Observations 1473 909 2740

Notes: Data comes from the Study of Consumer Purchases in the United States, 1935-1936 accessed on ICPSR.

38

Table 2: Relation between crop acreage and pellagra

log pellagra death rate

Geographic level: State (1910-1936) Counties in NC (1915-1936) and SC (1915-1925)

(1) (2) (3) (4) (5) (6) (7) (8)

Cotton acres per capita 0.0603***

0.189***

(0.0197)

(0.0669)

Corn acres per capita

-0.0242**

-0.160**

(0.00897)

(0.0651)

Peanut acres per capita

-0.0136*

0.00349

(0.00703)

(0.0212)

Sweet potato acres per capita

-0.0390***

-0.00467

(0.0104)

(0.00475)

State FE Yes Yes Yes Yes No No No No

County FE No No No No Yes Yes Yes Yes

Year FE Yes Yes Yes Yes Yes Yes Yes Yes

Revenue per acre of cotton Yes Yes Yes Yes Yes Yes Yes Yes

Observations 293 293 293 293 1906 1906 1906 1906

States or counties 19 19 19 19 117 117 117 117

Notes: Standard errors, reported in parentheses, are clustered at the state-level in columns (1)-(4) and at the county level in columns (5)-(8). Columns

(5)-(8) restrict to counties that harvested over 100 acres of cotton in the year 1889.

* p<0.1, ** p<0.05, *** p<0.01"

39

Table 3: Relation between cotton and food crops

Corn acres per

capita

Peanut acres

per capita

Sweet potato

acres per

capita

Corn acres per

capita

Peanut acres

per capita

Sweet potato

acres per

capita

Geographic level: State (1900-1936) Counties in NC (1915-1936) and SC (1915-1925)

(1) (2) (3) (4) (5) (6)

Cotton acres per capita -0.582*** -1.100* -0.127 -0.320*** -0.0134 0.00396

(0.178) (0.554) (0.155) (0.0685) (0.111) (0.130)

State FE Yes Yes Yes No No No

County FE No No No Yes Yes Yes

Year FE Yes Yes Yes Yes Yes Yes

Observations 575 575 575 1923 1923 1923

States or counties 19 19 19 118 118 118

Notes: Standard errors, reported in parentheses, are clustered at the state-level in columns (1)-(3) and at the county level in columns (4)-(6).

* p<0.1, ** p<0.05, *** p<0.01"

40

Table 4: The boll weevil and pellagra

log pellagra death rate

log typhoid

death rate

log

tuberculosis

death rate

log measles

death rate

Geographic level:

Counties in NC (1915-1950) and SC (1915-

1925). Column (4): only counties that

produced over 100 acres of cotton in 1889

Counties in NC (1915-1929)

(1) (2) (3) (4) (5) (6) (7) (8)

Post boll weevil -0.252*** -0.249*** -0.250*** -0.190*** -0.197*** 0.0321 0.0379 0.0205

(0.0532) (0.0500) (0.0535) (0.0553) (0.0601) (0.0600) (0.0397) (0.0470)

Post boll weevil * pre-boll weevil pellagra

death rate (1915-1916 average)

-0.287***

(0.0295)

Post boll weevil * pre-boll weevil cotton acres

per capita (1909)

-0.0371

(0.0401)

County FE Yes Yes Yes Yes Yes Yes Yes Yes

Year FE Yes Yes Yes Yes Yes Yes Yes Yes

Malaria Death Rate No No No No Yes Yes Yes Yes

Observations 3591 3591 3591 2931 1294 1294 1294 1294

Counties 130 130 130 118 100 100 100 100

Notes: Standard errors, reported in parentheses, are clustered at the county level.

* p<0.1, ** p<0.05, *** p<0.01"

41

Table 5: Enrichment Standards proposed by FDA (1941)

Minimum (mg) Maximum (mg)

Thiamine

1.1 1.8

Riboflavin

0.7 1.6

Niacin

10 15

Iron

8 12.5

Optional Ingredients:

Vitamin D

150 750

Calcium

300 800

Source: Food and Bread Enrichment 1949 - 1950; National Research

Council Committee on Cereals

42

Table 6: Voluntary fortification and pellagra

log pellagra death rate

Geographic level: State (1910-1950) Counties in NC (1915-1950)

(1) (2) (3) (4) (5) (6)

Post voluntary fortification -0.0211*** 0.00816 -0.0282** -0.184*** -0.184*** -0.203***

(0.00684) (0.00962) (0.0111) (0.0318) (0.0198) (0.0313)

Post voluntary fortification * pre-niacin pellagra

death rate (1932-1936)

-0.0576***

-0.254***

(0.00443)

(0.0240)

Post voluntary fortification * pre-niacin cotton acres

per capita

-0.0446***

-0.0570

(0.0126)

(0.0352)

State FE Yes Yes Yes No No No

County FE No No No Yes Yes Yes

Quadratic time trend Yes Yes Yes Yes Yes Yes

Observations 534 534 534 3394 3394 3394

States or counties 19 19 19 100 100 100

Notes: Standard errors, reported in parentheses, are clustered at the state-level in columns (1)-(3) and at the county level in columns (4)-(6).

* p<0.1, ** p<0.05, *** p<0.01"

43

Table 7: Fortification laws and pellagra

log pellagra death rate

Geographic level: State (1910-1950) Counties in NC (1915-1950)

(1) (2) (3) (4) (5) (6)

Post fortification law -0.0634*** 0.00386 -0.0558** 0.137*** 0.137*** 0.120***

(0.0207) (0.0114) (0.0218) (0.0300) (0.0422) (0.0324)

Post fortification law * pre-niacin pellagra death rate

-0.0552***

-0.188***

(0.00345)

(0.0215)

Post fortification law * pre-niacin cotton acres per

capita

-0.0169

-0.0509*

(0.0157)

(0.0269)

State FE Yes Yes Yes No No No

County FE No No No Yes Yes Yes

Year FE Yes Yes Yes No No No

Quadratic time tred No No No Yes Yes Yes

Observations 534 534 534 3394 3394 3394

States or counties 19 19 19 100 100 100

Notes: Standard errors, reported in parentheses, are clustered at the state-level in columns (1)-(3) and at the county level in columns (4)-(6).

* p<0.1, ** p<0.05, *** p<0.01"

44

Table 8: The boll weevil and height

Height

(1) (2) (3)

Post boll weevil 0.129 0.0940 0.0233

(0.0801) (0.0793) (0.0832)

Post boll weevil * state pellagra death rate (1928)

0.208***

(0.0717)

Post boll weevil * 1910 cotton acres per capita

0.179***

(0.0612)

County of birth FE Yes Yes Yes

Year of birth FE Yes Yes Yes

Year of enlistment FE Yes Yes Yes

Observations 217600 217600 217600

Counties 991 991 991

Notes: Standard errors, reported in parentheses, are clustered at the county level.

* p<0.1, ** p<0.05, *** p<0.01"

45

Table 9: Fortification and income

log income

(1) (2) (3)

Post enrichment law 0.0303 0.0165 0.0297

(0.0205) (0.0232) (0.0211)

Post enrichment law * pre-niacin discovery pellagra

death rate

0.0253***

(0.00653)

Post enrichment law * pre-niacin discovery cotton

acres per capita

0.00935

(0.00524)

Census year FE Yes Yes Yes

Year of birth FE Yes Yes Yes

Age FE Yes Yes Yes

State of birth FE Yes Yes Yes

State of residence FE Yes Yes Yes

Observations 90364 90364 90364

States of birth 11 11 11

Notes: Standard errors, reported in parentheses, are clustered at the state of birth level.

* p<0.1, ** p<0.05, *** p<0.01"