Geochemical Environments and 

Cardiovascular Mortality Rates 

in Georgia

GEOLOGICAL SURVEY PROFESSIONAL PAPER 574-C

Prepared in cooperation with the 

U.S. Public Health Service
Geochemical Environments and 

Cardiovascular Mortality Rates 

in Georgia

By HANSFORD T. SHACKLETTE, HERBERT I. SAUER, and A. T. MIESCH 

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

GEOLOGICAL SURVEY PROFESSIONAL PAPER 574-C

Prepared in cooperation with the 

U.S. Public Health Service

A study of the chemical elements 

in soils and plants from counties that have 

contrasting rates for diseases of the heart 

and blood vessels

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHINGTON : 1970
UNITED STATES DEPARTMENT OF THE INTERIOR 

WALTER J. HICKEL, Secretary

GEOLOGICAL SURVEY 

William T. Pecora, Director

For sale by the Superintendent of Documents, U.S. Government Printing Office 

Washington, D.C. 20402 - Price 50 cents (paper cover)
CONTENTS

Abstract. _______________________________

Introduction. ___________________________

Cardiovascular mortality rates in Georgia. _.

Physiography, geology, and soils of Georgia.

Collection and analysis of geochemical data. 

Sample design.. _ ____________________

Sampling media. ____________________

Soils. ____-_--_-_-__--_-_____

Procedures used in chemical analysis

Methods of statistical analysis. .__ __

Results of analyses.

Compositions of vegetables and garden soils.

Page 

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1

2

4

6

6

9

9

9

10

10

13

13

Page 

Results of analyses Continued

Compositions of trees and uncultivated soils...... C13

Correspondence between the compositions of plants 

and soils..__---__-__--------______----._------ 13

Vegetables and garden soils._________-__--_-_ 19

Trees and uncultivated soils.._____-__--___.__ 25

Correspondence among the compositions of soil 

horizons _____________________________________ 31

Correspondence between the compositions of stems

and leaves of trees.___________________________ 34

Summary. _________________________________________ 34

Conclusions.___-__-_-____-__-__-_____--_----____-__ 38

Literature cited.___________________________________ 39

ILLUSTRATIONS

FIGURE 1. Map showing physiographic regions and provinces in Georgia, and locations of counties with high and low 

death rates per 100,000 population for cardiovascular diseases._______________________________________

2. Map showing Great Soil Groups of Georgia, and the locations of counties that have high and low cardiovascular 

mortality rates.____________-________-_____________________-___-______-_---______-__----_----_

3-7. Diagrams showing:

3. Correlations between the amounts of elements in garden soils and the amounts in vegetables________

4. Correlations between the amounts of elements in the C horizon of uncultivated soils and the amounts 

in the A and B soil horizons and in the stems and leaves of trees_------_-------__------__---_

5. Correlations between the amounts of elements in the B horizon of uncultivated soils and the amounts 

in the A horizon of soils and in the stems and leaves of trees_______________________________

6. Correlations between the amounts of elements in the A horizon of uncultivated soils and the amounts 

in stems and leaves of trees____---_-_____________________________________________________

7. Correlations between the amounts of elements in stems and in leaves of trees._____________________

Page

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20

22

28

32

36

	TABLES

Page

TABLE 1. Death rates for selected causes, white males age 35-74, selected counties of Georgia, during the period 1950-59. C3

2. Localities, kinds, and numbers of samples that were collected in Georgia______-__---_-_____----__----_-_- 8

3. Analytical limits of detection.____________________________________________________________________ 10

4. Components of logarithmic variance between samples, sites, and areas.__________________-_-___---_-_---_ 12

5. Ash contents of vegetables and element contents of vegetable ashes and garden soils____________---_-___-- 14

6. Ash contents of trees and element contents of tree ashes_____________-________-___--__-----------_----- 16

7. Element contents of uncultivated soils._________________________________________-_____----_-----_--- 18

8. Correlations between the amounts of elements in vegetables and garden soils._________._____-__---_----._- 19

9. Correlations between the amounts of elements in trees and in the C horizon of uncultivated soils.__________ 26

10. Correlations between the amounts of elements in trees and in the B horizon of uncultivated soils-__________ 26

11. Correlations between the amounts of elements in trees and in the A horizon of uncultivated soils___________ 34

12. Correlations between the amounts of elements in horizons of uncultivated soils.__________________________ 34

13. Correlations between the amounts of elements in stems and leaves of trees.____________________-------_-- 38

ni

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

GEOCHEMICAL ENVIRONMENTS AND CARDIOVASCULAR 

MORTALITY RATES IN GEORGIA

By HANSFORD T. SHACKLETTE, HERBERT I. SAUER, and A. T. MIESCH

ABSTRACT

Nine contiguous counties of northern Georgia that have a low 

cardiovascular mortality rate lie in an area where the rocks, by 

weathering, continuously contribute a supply of minor elements 

to the soil that is formed. Nine counties of central and southcentral Georgia, in contrast, have a high cardiovascular mortality 

rate, and the soil is largely composed of materials that generally 

are deficient in weatherable minerals. The concentrations of the 

elements that were studied in both garden soils and uncultivated 

soils from the two areas tend to be significantly different and 

are generally higher in the low-death-rate area. The difference in 

element composition of soils from the two areas is not apparent 

in analyses of most vegetables; only cabbage and green beans 

tend to reflect, on a broad scale, the compositional differences in 

amounts of certain elements in soils. The concentrations of most 

elements in tree samples tend to be higher in the low-rate area; 

therefore, trees appear to be more sensitive than vegetables to 

the variation in element content of soils. The difference between 

the two areas in the levels of various chemical elements present 

in vegetables appears to be so slight as to be unlikely to contribute 

appreciably to the observed differences in death rates in middleaged humans. The chemicals in soils, however, may enter the 

human food chain in water, in food plants that were not sampled 

in this study, and in meat and milk from animals that have fed 

on cultivated forage plants and native vegetation. If geochemical differences between the two areas do, in fact, have a causal 

relationship to death from cardiovascular diseases, the cause 

would appear to be a dietary deficiency, rather than an excess, 

of the elements that were studied.

INTRODUCTION

The counties of Georgia that have low rates of cardiovascular mortality are in the northern part of the State, 

whereas those that have high rates are in the southern 

and central parts. Northern and southern counties are 

very different in their characteristic geological formations and soil types. The fact that the two areas of contrasting mortality rates coincide, with two areas of contrasting physiography gave rise to the hypothesis that 

cardiovascular mortality might be causally related to 

physical factors of the environment. Of these factors, 

the chemical composition of the surficial deposits and 

the vegetation appeared likely to have the greatest effect

on the human inhabitants of a region. At the beginning 

of this study, the patterns of heart-disease mortality 

rates in this State were well known; the chemical element contents of soils and plants, on the other hand, 

were but poorly known. Therefore, the Heart Disease 

and Stroke Control Program of the U.S. Public Health 

Service and the U.S. Geological Survey undertook a cooperative study of the geochemical properties of soils 

and plants as they relate to the occurrence of cardiovascular mortality in Georgia.

A preliminary survey was made in the summer of 1963 

in which rocks, uncultivated soils, and native plants were 

sampled in counties that have low, intermediate, and 

high rates of heart-disease mortality. These samples 

were analyzed chemically, and the results of the analyses indicated that the areas of high and low mortality 

rates could be identified by the amounts of certain elements that were in samples from the areas (Shacklette 

and Sauer, 1964). Following this study, a more rigorous 

design for sampling, which included sampling of garden 

soils and vegetables as well as uncultivated soils and 

native plants, was devised for the areas under study, and 

fieldwork was completed in the summer of 1965. The results obtained from chemical analyses of the samples, 

and the abundance of the elements in the areas of high 

and low mortality rates, are presented in this report.

Interest in the relation of the environments in Georgia 

to human health began early in the history of the State 

and continued up to the time of the Civil War. Cramer 

(1967) gave an account of the papers that reflect this 

interest. Most early reports were prepared by physicians 

who were careful to note the effects of physiography on 

the prevalence of diseases and the occurrence of epidemics. Yellow fever and malaria were the two diseases 

most commonly reported to have been associated with 

topographic features because they were more prevalent 

in areas of low-lying, swampy ground than in welldrained upland areas. Methods of clearing the land of

Cl
C2 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

trees and cultivating the soil that resulted in impeding 

the flow of streams and increasing the amount of standing water caused an accompanying increase in incidence 

of these diseases. Putrefaction of vegetation in wet locations was thought to produce a noxious effluent that 

caused the diseases; the fact that mosquitoes, which 

breed in standing water, are the vectors in the transmission of these diseases was not known at the time.

Speculation on the association of health problems 

with geological features, however, was not limited to 

specific diseases. Cramer (1967, p. 216) quoted a report 

that was read to the Georgia Medical Society in 1806 

by Dr. Joshua E. White, who said,

To obtain a correct knowledge of medical topography, we should 

possess some information respecting the face of the country; its 

elevations and depressions, the quality and proportion of low 

and high grounds; the number and magnitude of the streams; 

and various other local circumstances. In relating facts, and 

detailing alterations which have been produced by the art and 

industry of man or by fortuitous causes, on the surface of the 

country, we should not confine our views solely to the present 

moment. To those who succeed us, it may be satisfactory to be 

informed what was, and thus they may be enabled to calculate 

what may be.

Cramer (1967, p. 217-218) reported further that as 

early as 1837 physicians had recognized the difference 

in disease rates between the Coastal Plain and the Piedmont regions and that the healthful environment of 

northern Georgia counties had been noted in 1853 by 

Dr. Robert C. Ward, who related the effects of lithology 

and topography on the properties of soil that was 

formed.

Geochemical characteristics of regions are, in the final 

analysis, expressions of bedrock geology and the concomitant changes produced by pedological and biological processes that relate to climate and the passing of 

time. An understanding of these characteristics is necessary in assessing the factors that control the chemical 

environment of a region. The data included in this report illustrate some chemical relationships of soils to 

their geologic parent materials and of plants to the soils 

that support them. The distribution and chemical behavior of elements in the system "rock-soils-plants" is 

a subject of increasing concern in several other types of 

geological investigations. For these reasons, these data 

are of geochemical and biogeochemical interest, independent of their possible usefulness in interpreting patterns of human disease mortality.

Shacklette, a botanist of the U.S. Geological Survey, 

directed this project and made the field studies; Miesch, 

a geologist of the same organization, devised and conducted statistical studies of the data; and Sauer, a 

statistician of the U.S. Public Health Service, provided 

all data on disease mortality rates and assisted in constructing the sampling plan and in interpreting the 

data.

We express our appreciation to Messrs. David F. 

Davidson and James A. Banta for their assistance in 

initiating and planning the study, to Messrs. Todd 

Church and John R. Keith for their help in collecting 

and preparing samples, to Messrs. Gary L. Seiner, Robert Terrazas, and George Van Trump for assistance in 

computer programming, and to Mmes. Josephine G. 

Boerngen, Jessie M. Bowles, and Dorothy Moore and 

Mr. Darrel Parke for their contributions to data processing and analysis. The following chemists of the Geological Survey analyzed the samples: J. C. Hamilton, 

Thelma F. Harms, J. B. McHugh, Harriet G. Neiman, 

Clara S. E. Papp, A. L. Sutton, Jr., Barbara Tobin, 

and J. H. Turner.

We also acknowledge the cooperation of the many 

property owners in Georgia who freely gave us permission to obtain samples on their land; without their generosity this study could not have been made.

CARDIOVASCULAR MORTALITY RATES IN GEORGIA

Death rates for the cardiovascular (CV) diseases include those for coronary heart disease (which accounts 

for more than half of all CV deaths), stroke, hypertensive diseases, and other diseases of the heart and 

blood vessels. Rates have been computed for the State 

of Georgia by usual county of residence, utilizing all 

deaths for the period 1950-59, inclusive (Sauer and 

others, 1966). Standard vital statistics techniques have 

been used in computing rates, which are expressed as 

average annual death rates per 100,000 population at 

risk, along with several refinements to meet the specific 

needs of this type of ecological study. The age-sex group 

of greatest epidemiological concern is middle-aged 

white males, which may be defined broadly as 

white males age 35-74. Rates have been computed for 

this age group, using the average of the 1950 and 1960 

censuses as the population at risk, and have been adjusted by the direct method by 10-year age groups to 

the total United States population of that age in 1950 

(Linder and Grove, 1943, p. 66-68). Differences in rates 

are, therefore, not due to differences in the age, sex, or 

race composition of the population of the various 

counties.

The high-rate counties have mortality rates for the 

cardiovascular diseases roughly double, and in some instances more than double, the rates for the low-rate 

counties. In this one State, contrasts are found that are 

almost as great as those for the entire United States 

(Sauer, 1962). Rates for 1949-51 by economic subregions show northern Georgia in a very low death-rate 

area and south-central Georgia in a very high rate area 

(Enterline and other, 1960, p. 762).
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C3

The nine contiguous low-rate counties chosen for this 

study are listed in table 1. The cardiovascular diseases 

death rate for white males age 35-74 ranged from 560 

to 682. Only three other counties of the 159 counties in 

Georgia had rates equally low Irwin, Liberty, and 

Miller; each of these three has very small populations 

of middle-aged white males, and these counties are isolated from other low-rate counties, therefore the possibility is strongly suggested that the low rates for these 

three counties are phenomena of chance fluctuation or 

random error.

Eighteen counties are listed as "high-rate," with 

death rates from 1,151 to 1,446; the first nine counties 

in this list were chosen for the study because they are 

rural counties in the section of the Sate which consistently had high rates. Two metropolitan counties, Chatham (including the city of Savannah) and Eichmond 

(including Augusta), were not included because soils 

and locally grown plants are presumed to have a lesser 

effect upon the risk of dying in urban areas than in rural 

areas. Five scattered counties were not included because 

they are surrounded by counties that have more moderate rates, which again suggests the possibility of 

chance fluctuation of rates.

The determination of the underlying cause of death 

frequently may be difficult, and the available diagnostic 

information may not always be adequate. For a broad 

group of diseases, such as the CV diseases, the available 

evidence suggests that this potential shortcoming does 

not invalidate the comparison of the counties that we 

selected (Sauer and Enterline, 1959). The rates for 

"all non-CV" causes follow a pattern similar to that 

for CV diseases (table 1). Of the nine counties with 

low CV rates, all but one had "all non-CV causes" rates 

below the State average, and of the nine counties 

selected with high CV rates, all but two had rates for 

all non-CV causes above the State rate. The factors 

which are causing these differences in cardiovascular 

disease rates are presently unknown, but whatever they 

are, they (or factors associated with them) tend to 

produce a somewhat similar pattern of rates for nonCV causes. Similar findings are presented in greater 

detail for the nation as a whole by Sauer and Enterline 

(1959) and Sauer and Brand (unpub. paper by H. I. 

Sauer and F. E. Brand, "Geographic differences in 

cause-specific death rates," presented to the Society for 

Epidemiologic Research, Washington, D.C., May 10, 

1968).

The all-causes death rates, therefore, show almost 

as much contrast as do the rates for the cardiovascular 

diseases. Several counties, in fact, in the high-deathrate area have all-causes rates approximately double 

those for several counties in the low-death-rate area 

(table 1). In general, the all-causes death rates for the

TABLE 1. Death rates for selected causes, white males age 35-74, 

selected counties of Georgia, during the period 1950-59

[Average annual death rates per 100,000 population, age adjusted by 10-year age groups 

by the direct method to the entire United States population age 35-74 in 1950. 

Deaths tabulated by Georgia State Department of Health, by county of usual 

residence]

Cardiovascular diseases 

(330-334, 400-468 »)

County

Low-rate counties:

Hall................

High-rate counties that 

were studied:

Jenkins.... _ ......

Warren. _ .........

Other high-rate 

counties:

Treutlen... ........

All counties of

All nonCoronary Other cardio- All 

Total heart cardio- vascular causes 

disease vascular causes of death 

(420 i) diseases of death

671.0 

655.2 

635.7 

647.5 

667.7 

680.8 

681.7 

587.6 

560.1

1,302.2 

1, 205. 5 

1,167.0 

1,206.3 

1,167.8 

1,446.4 

1, 151. 2 

1, 330. 8 

1,321.7

1, 218. 8 

1, 177. 2 

1, 170. 3 

1, 170. 6 

1,162.3 

1, 155. 8 

1, 252. 1 

1, 203. 0 

1, 171. 7

925.2

344.1 

262.2 

275.1 

296.9 

328.6 

274.8 

332.2 

201.2 

287.1

743.1 

650.6 

603.7 

569.4 

467.4 

701.1 

679.3 

530.1 

915.6

781.5 

753.7 

644.1 

754.5 

614.6 

667.2 

572.2 

773.5 

533.2

520.4

326.9 

393.0 

360.6 

350.6 

339.1 

406.0 

349.5 

386.4 

273.0

559.1 

554.9 

563.3 

636.9 

700.4 

745.3 

471.9 

800.7 

406.1

437.3 

423.5 

526.2 

416.1 

547.7 

488.6 

679.9 

429.5 

638.5

404.8

525.4 

607.9 

529.6 

485.4 

573.3 

593.6 

735.5 

480.0 

477.5

789.9 

546.0 

834.3 

736.1 

731.5 

568.6 

677.9 

802.5 

760.2

744.7 

757.2 

700.1 

927.8 

638.1 

686.6 

618.1 

771.3 

766.2

649.0

1,196.4 

1,263.1 

1,165.3 

1, 132. 9 

1,241.0 

1,274.4 

1,417.2 

1, 067. 6 

1,037.6

2,092.1 

1,751.5 

2, 001. 3 

1, 942. 4 

1, 899. 3 

2, 015. 0 

1,829.1 

2, 133. 3 

2, 081. 9

1,963.5 

1,934.4 

1, 870. 4 

2,098.4 

1,800.4 

1,842.4 

1,870.2 

1,974.3 

1,937.9

1, 574. 2

1 Code number of International Statistical Classification of Diseases, 7th Revision 

(World Health Organization, 1957).

2 With adjustments for resident institution populations.

low-rate counties are similar to or lower than the CV 

diseases rates alone for the high-rate counties.

Calculation of death rates for the CV diseases for 

1959-61 indicates that all nine high-rate counties have 

rates which are above the United States rate and which 

are roughly 70 percent higher than the rates for the lowrate counties.

For 1950-59, the pattern of rates for white females 

age 35-74 tended to be similar to that for males. Since 

there are fewer deaths among white females, however, 

chance fluctuation will tend to be higher (Lilienfeld 

and others, 1967, p. 121-126). Of the nine counties 

selected because of their low male death rates, seven 

had rates for white females below the State average, 

several of the rates being among the lowest in the State. 

Of the nine counties selected because of their high male 

death rates, seven also had white female rates higher 

than the State average. Although nonwhite rates tend 

to a considerable extent to present patterns parallel to 

those for whites, the number of nonwhites in the northern Georgia counties is generally too small to provide a 

basis for calculating meaningful rates.
C4 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

These contrasts in rates are in general not due to 

random error, and thus far show no evidence of being 

due to methods of data collection or classification and 

we have made extensive search for such evidence. There 

is an incentive, therefore, to search for and test hypotheses regarding factors which may be responsible for 

these differences.

The death rates tell us that the risk of dying of CV 

diseases in middle age is twice as great in the high-rate 

area as in the low-rate area. The rates do not, however, 

tell us whether the attack rate is higher in the high-rate 

area, or whether these diseases are more lethal in this 

area, or both. It is possible that the attack rate or incidence rate in the high-death-rate area is higher than 

in the low-death-rate area, or it may be that the time 

period between onset of clinical disease and death is 

shorter that is, that the lethality or fatality rate is 

higher; it is also possible that both the attack rate and 

the fatality rate are somewhat higher in the high-rate 

areas than in the low.

The nine counties in the northern part of the State 

that have very low death rates due to CV causes are 

identified in figure 1. They are part of a group of closely 

associated or contiguous low-rate counties in the Blue 

Eidge, the Valley and Ridge, and the upper part of the 

Piedmont provinces. The nine counties with very high 

death rates are likewise part of a group of contiguous or 

closely associated high-rate counties in the east-central 

part of the State; all counties but, one lie entirely within 

the Atlantic Coastal Plain region. The counties that 

were chosen for this study give substantial evidence that 

they are properly classified. As a further illustration: 

Of the 159 counties in Georgia the low-rate counties are 

all among the 20 lowest for all causes of death as well as 

among the very lowest for the cardiovascular diseases 

generally, and coronary heart disease specifically. 

Similarly, the high-rate counties are all among the 20 

highest for all causes of death.

PHYSIOGRAPHY, GEOLOGY, AND SOILS OF GEORGIA

The northern part of the State lies within four provinces of the Appalachian Highlands region, and the 

southern part is in the Atlantic Coastal Plain region 

(U.S. Geological Survey, 1968), as is shown in figure 1. 

These regions are characterized by features of relief and 

geologic formations (Georgia Division of Mines, Mining and Geology, 1939) that have been largely responsible for the differences in soils within the State. The 

Southern Appalachian region, according to Laurence 

(1968, p. 156), comprises four major geologic provinces 

whose boundaries are almost identical with those of the 

four physiographic provinces, therefore the same names 

may be used for both kinds of provinces. The Appalachian Plateaus province barely extends into the extreme 

northwestern part of the State, where high, narrow 

ridges of sandstone occur interbedded with layers of 

shale. This province was not sampled in this study.

The Valley and Ridge province is characterized by 

long, narrow ridges that parallel broad valleys, which 

have a northeast-southwest trend. The folded and 

faulted sedimentary rocks range in age from Early Cambrian to Pennsylvanian. The Cambrian, Ordovician, 

and Mississippian Systems include thick and extensive 

deposits of carbonate rocks. Clastic rocks predominate 

in the Lower Cambrian, Middle Ordovician, Silurian, 

Devonian, Lower Mississippian, and Pennsylvania!! 

(Laurence, 1968, p. 158). Soils derived from limestones 

in the valleys generally are rich loams that are suitable 

for agriculture. The noncalcareous shales produce a soil 

that is less fertile than that derived from limestone, and 

the soils that have sandstone parent materials are relatively infertile (Carter and Giddens, 1954).

The Blue Ridge province in the northeastern part of 

the State is characterized by high mountains, narrow 

valleys, and rapid streams. The rocks range from crystalline gneisses and schists to unmetamorphosed clastic 

sedimentary rocks of late Precambrian and Early Cambrian age. Igneous rocks of Paleozoic age, from peridotite to granite, are widespread in this province (Laurence, 1968, p. 156-157). The cool climate of the high 

elevations has favored the retention of organic matter 

in the generally acid soils, but the great relief of the 

region does not promote large-scale agriculture, therefore subsistence farms are prevalent.

The Piedmont province extends from the foot of the 

Appalachian Mountains to the fall line at the coastal 

plain and constitutes about one-third of the State. This 

province includes a wide variety of Precambrian and 

Paleozoic metamorphic rocks, and intrusive rocks of 

several different ages. Much of the area has been deeply 

weathered, and saprolite conceals the unweathered bedrock at places (Laurence, 1968, p. 156). The soils of the 

part of the province that was sampled in this study 

commonly are sandy loams, but at places erosion lias 

exposed clay subsoils.

Southern Georgia and parts of central Georgia lie 

within the Atlantic Coastal Plain region. The landscape 

has but little relief, and swamps and sluggish streams 

are common. The typically sandy soils overlie marine 

rocks of Cretaceous and Tertiary age. These rocks, 

especially where exposed, have been subjected to intensive weathering. The counties that were studied, if low 

lying, were largely covered with swamp forests; those 

with greater relief and better drainage were devoted to 

small-scale diversified agriculture.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA

EXPLANATION

C5

p 

I /e^--v < A

FIGURE 1. Physiographic regions and provinces in Georgia, and locations of counties with high and low death rates per 100,000 

population for cardiovascular diseases among white males of ages 35-74 during the period 1950-59.

368-640 O 7C
C6 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

The kinds of soils that occur in Georgia were shown 

on a map prepared by the U.S. Soil Conservation Service (1969), which utilized the new soil classification 

system that was established by the Soil Survey Staff 

(1960, 1967). This map classified soils into the four 

highest categories (Order, Suborder, Great Group, and 

Subgroup) of the hierarchical system. The lowest of 

these categories, Subgroup, is distinguished principally 

by degree of slope and combinations of other Great 

Groups that are given for the map unit. For simplicity 

of presentation in this report, Subgroups have been 

ignored in preparing the classification outline and the 

soils map (fig. 2) that follow.

ORDER Entisols Soils that have no pedogenic horizons.

Suborder Psamments Entisols that have textures of loamy

fine sand or coarser.

Great Group Quartzipsamments Psamments that consist almost entirely of minerals highly resistant to 

weathering, mainly quartz.

ORDER Histosols Wet organic (peat and muck) soils. 

Suborder (not named) Histosols of warm regions.

Great Group (not named) Plant residue highly decomposed. 

ORDER Inceptisols Soils with weakly differentiated horizons

showing alteration of parent materials. 

Suborder Aquepts Seasonally wet Inceptisols that have an 

organic surface horizon and a sodium saturation, mottles, or gray colors. 

Great Group Humaquepts Aquepts that have an acid

dark surface horizon (in Georgia, tidal marshes). 

Suborder Ochrepts Inceptisols that have formed in materials with crystalline clay minerals, have light-colored 

surface horizons, and have altered subsurface horizons that have lost mineral matter. 

Great Group Dystrochrepts Ochrepts that are usually 

moist and low in bases and have no free carbonates 

in the subsurface horizons.

ORDER Spodosols Soils with low base supply that have in 

subsurface horizons an accumulation of amorphous materials consisting of organic matter plus compounds of aluminum and usually iron. 

Suborder Aquods Seasonally wet Spodosols.

Great Group Haplaquods Aquods that have a subsurface horizon that contains dispersed aluminum and 

organic matter, but only small amounts of free iron 

oxides. 

ORDER Ultisols Soils with horizons of clay accumulation and

low (base supply.

Suborder Aquults Seasonally wet Ultisols that have mottles, iron-manganese concretions, or gray colors. 

Great Group Ochraquults Aquults that have a lightcolored or thin black surface horizon.

Suborder Udults Ultisols that are usually moist, relatively 

low in organic matter in the subsurface horizons; 

formed in humid climates that have short or no annual dry period.

Great Group Hapludults Udults that have a thin subsurface horizon of clay or appreciable weatherable 

minerals, or both.

Great Group Paleudults Udults that have a thick 

horizon of clay accumulation without appreciable 

weatherable minerals.

The counties that have a low cardiovascular mortality 

rate are in an area where Hapludults predominate (fig. 

2). The principal characteristic, from the geochemical 

standpoint, of soils in this Great Group is their content of weatherable minerals which serve as a constant 

source of element enrichment in the process of soil development. The counties that have a high mortality rate 

for these diseases are located in areas where one of the 

three soils, Paleudults, Quartzipsamments, and Ochraquults, predominates. Paleudults are characterized by 

the absence of appreciable amounts of weatherable 

minerals, Quartzipsamments consists mostly of 

minerals that are highly resistant to weathering, and 

Ochraquults are deficient in available elements because 

of their high seasonal water content which causes excessive leaching. Soils in the low-death-rate counties, 

therefore, were expected to contain certain elements in 

greater abundance than is found in soils from the highdeath-rate counties. The analyses given in this report 

support this hypothesis.

Most soils of Georgia are not very fertile as judged 

by agricultural standards in their natural condition. 

This infertility was attributed by Carter and Giddens 

(1954) to climatic conditions and soil development 

processes. The soils generally are deficient in the major 

elements for plant nutrition, as well as in magnesium, 

boron, and zinc; therefore, trace elements commonly are 

added to the fertilizers used on certain crops.

The relation of the two areas of contrasting rates of 

heart disease mortality to the occurrence of soil types 

can be summarized by stating that the high-mortality 

counties have soils that are derived from the highly 

weathered marine sediments of the coastal plains, 

whereas the low-mortality counties have soils that 

originated from a great variety of rock types from which 

weathering is continuously providing a fresh supply 

of chemical elements to the soils.

COLLECTION AND ANALYSIS OF GEOCHEMICAL DATA

SAMPLE DESIGN

The counties of Georgia to be sampled were divided 

into two groups of nine counties each, according to their 

classification by rates of death due to heart disease. The 

counties that have high death rates are Bacon, Bleckley, Burke, Dodge, Emanuel, Jeff Davis, Jefferson, 

Jenkins, and Warren; those with a low death rate are 

Cherokee, Fannin, Forsyth, Gilmer, Hall, Murray, 

Pickens, Towns, and Union. Within each of the two 

groups, 30 sites were selected for sampling native plants 

(trees) and uncultivated soils, and 30 sites were chosen 

for sampling vegetables and garden soils. This made a 

total of 120 sample sites in the two areas.

A sample site for trees and uncultivated soils was 

defined as an area in which the required species of trees
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA

EXPLANATION

C7

Quartzipsamments Humaquepts

Plant residue highly Dystrochrepts

'1 L. 1 /MWWS ^ - 5T^

FIGURE 2. Great Soil Groups of Georgia, and the locations of counties that have high and low cardiovascular mortality rates.
C8 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

could be found rooted in a soil unit which was judged 

to be relatively homogeneous. Ordinarily, the sample 

site was considered to be within a radius of 20-60 feet 

of the point that was selected for the soil-sample hole; 

however, this radius was extended at places in order 

to include a required species of tree, if the same soil unit 

continued into this enlarged area. A sample site for vegetables and garden soils was defined as a single home 

garden (not a commercial truck farm). The size of these 

gardens ranged from about 400 square feet to a quarter 

acre (10,890 sq. ft).

The distribution of sample sites by counties within 

each area (the high and low-death-rate areas) was arbitrarily set at three native plant and soil sites and three 

garden sites for each of six counties of an area, and four 

native plant and soil sites and four garden sites for each 

of three counties (table 2). Within a county the exact 

location of sample sites was dictated, to a large extent, 

by the restrictions of the sampling plan that is, the 

locations of the sites often were determined by the limited occurrence of the required sampling media. The 

selection of sites for sampling native plants and uncultivated soils first required that relatively undisturbed 

forests be found in which the selected species of trees 

and a reasonably homogeneous soil unit occurred. The 

selection of garden sites was controlled largely by the 

requirements that the kinds of vegetables that were

wanted occurred in each garden and that permission of 

the owner to sample the garden was obtained. The 

former requirement was at places difficult or impossible 

to meet, therefore complete suites of samples were not 

obtained at all sites. Permission to sample gardens was 

almost invariably given by the owners, many of whom 

assisted us in gathering the vegetable samples.

Within the limitations imposed on selection of sites 

as described above, we attempted to obtain samples that 

were representative of a county. In effect, the unpredictable occurrence of suitable sites contributed a degree of 

randomness to the sampling plan.

The two sampling areas are disposed in a northsouth orientation and, therefore, encompass a wide 

range of climates, soils, forest types, plant species, and 

cultural preferences. In the most southern counties, 

where the fieldwork began, we collected samples of persimmon, blackgum, black cherry, red maple, blackjack 

oak, smooth sumac, sassafras, and sweetgum. Of these 

eight species, only five (blackgum, persimmon, red 

maple, smooth sumac, and black cherry) could be found 

at all sites throughout the State (table 2). Blackjack 

oak was found at all sites in the high-death-rate area, 

but did not occur at all sites in the low-death-rate area; 

therefore, two other species of oak (black oak and post 

oak) that are closely related morphologically were substituted in the latter area. Sassafras was more abundant

TABLE 2. Localities, kinds, and numbers of samples that were collected in Georgia

[---., no samples collected]

Kinds and numbers of samples

Native trees ' Vegetables Uncultivated soils Gar- Soils,

den compoBlack- Per- Red Sassa- Smooth Sweet Black Black- Cab- Green Lima Toma- ABC soils, nentsof

gum Oak 2 sim- maple fras sumac gum cherry eyed bage 3 Corn beans beans toes hori- hori- hori- plow variance

mon peas zon zon zon zone study

High-death-rate area

Burke _ .......

Dodge

Subtotal ..

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

1 

3

4 

3 

1

3 

1

1 

1

18

3 

3 

4 

3 

4 

3 

4 

3 

3

30

2 

3 

4 

2 

4 

3 

4 

3 

3

28

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

2 

3 

4 

3 

3 

3 

4 

3 

3

28

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 

3 

4 

3 

4 

3 

4 

3 

3

30

3 - 

4

4 ....

3 - 

4 

3 

3

30

12

6 

6 

6

30

Low-death-rate area

Cherokee _ .

Fannin _ .. ..

Gilmer _ ..

Hall.. ........

Towns. .. ---. .

Subtotal ..

Total... _.

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

3 

3 

3 

4 

2 

3 

3 

3 

3

27

45

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4

4 

3 

3

1 

2

4 

3 

3 

4 

4 

3 

3 

3 

3

27 30

55 60

1

1

1

1

4

34

4 

3 

3 

4 

4 

3 

3 

3 

3

30

58

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4

3

4 ..

4 

3 

3 

3

30

60

4

3

4 

1 

2 

1

15

45

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4 

3 

3 

4 

4 

3 

3 

3 

3

30

60

4

3 .

4 

4 

3

3 ....

3 

3

30

60

6

6 

6 

6

6

30

60

1 Tree samples were divided into stems and leaves, and these were analyzed separately; therefore the total number of tree samples is twice that shown

2 Includes 44 samples of blackjack oak, 13 samples of post oak, and 3 samples of black oak.

3 Both cabbage and collards are included; they are botanically similar.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C9

in northern Georgia than in southern Georgia however, a complete suite of samples could not be obtained in 

either area. Sweetgum was absent from only five sites.

Of the six kinds of vegetables that were studied, only 

corn, green beans, and tomatoes could be found in all 

gardens that were sampled, although cabbage (or collards) was absent from only two of the 60 gardens. 

Regional differences in preference for vegetables were 

most obvious with blackeyed peas. This vegetable was 

found in all 30 gardens that we sampled in the southern area, but in only four gardens in the northern area. 

Similarly, lima beans were found in all southern gardens, but in only half of the northern gardens. Of the 

vegetables that were observed but not sampled because 

of their immaturity at the time of the field study and 

their infrequent occurrence, Irish (white) potatoes were 

rarely seen in the southern gardens, and sweet potatoes 

(yams) were uncommon in the north.. Other vegetables 

that were observed, but which occurred erratically, included squash, peppers, beets, peanuts, okra, cucumbers, 

eggplant, and melons. Corn and tomatoes were found 

in almost all gardens that were examined and were by 

far the most common vegetables throughout the State.

SAMPLING MEDIA 

PLANTS

The kinds of plants that were sampled, and their 

scientific names (Fernald, 1950), are listed below:

Blackgum, Nyssa sylvatiea Marsh.

Blackjack oak, Quercus marilandica Muench.

Black oak, Quercus velutina Lam.

Post oak, Quercus stcllata Wang.

Persimmon, Diospyros virginiana L.

Red maple, Acer rubrum L.

Sassafras, Sassafras albidum (Nutt.) Nees

Sumac, Rhus glabra L.

Sweet gum, Liquidambar styraciflua L.

Black cherry, Prunus serotina Ehrh.

Blackeyed peas, Vigna sinensis Endl. (samples included several cultivated varieties)

Cabbage, Brassica oleracea var. capitata L.

Collards, Brassica, oleracea var. acephala DC.

Corn, Zea mays L. (samples included both field corn and 

sweet corn)

Green beans, Phaseolus vulgaris L. (samples included both 

green-pod and yellow-pod varieties)

Lima beans, Phaseolus limcnsis Macfad. (samples included 

both the bush form and the climbing form)

Tomato, Lycopcrsicum csculcntum Mill, (all samples were 

of the common red-fruited form)

The tree samples were stems (terminal parts of 

branches) about 12 inches long. The leaves were removed from the stems, and the leaves and the stems 

were analyzed separately. Both types of tree samples 

were analyzed, because it is known that some chemical 

elements are concentrated in stems, whereas others are

concentrated in leaves. The samples were air dried, 

pulverized in a Wiley mill, weighed, and burned to 

ash in an electric oven in which the heat was increased 

50° C per hour to a temperature of 550° C and held 

at this temperature for 14 hours. The ash was then 

weighed to determine the ash yield of the dry plant 

sample and was used in all subsequent analytical 

procedures.

The vegetable samples were prepared in the same 

manner as for table use; that is, the blackeyed peas were 

shelled and a few tender pods were left with the seeds, 

the cabbage and collards leaves were washed and cut, 

the corn grains were cut from the cobs, the pods of 

green beans were washed and broken into pieces, the 

lima beans were removed from the pods, and the tomatoes were washed and sliced. The prepared vegetables 

were packed in polyethylene bags as soon as possible 

after preparation and shipped by air to the Denver 

laboratories of the U.S. Geological Survey where they 

were oven dried to constant weight. Most vegetables, 

because of their content of sugar or colloids, or both, 

are difficult to air dry, in contrast to stem and leaf 

samples which air dry readily. The dried vegetable 

samples were pulverized and burned to ash in the same 

manner as the tree samples.

SOILS

In this report, soil-horizon terminology follows the 

traditional usage of the A and B horizons to designate 

divisions of the solum and of the C horizon to designate 

soil parent material (Baldwin and others, 1938). The 

uncultivated soils, at the tree-sample sites, were sampled 

from holes made by a clamshell digger to the depth 

necessary to include the C horizon of the soil. This 

depth ranged from less than 1 foot to 3 feet. The samples 

of the A and B horizons were taken from the sides of 

the holes by using1 a trowel, and the C horizon sample 

was taken from the bottom of the hole with the digger. 

Zonation ordinarily was well defined; some lithosols of 

the mountainous provinces and the regosols of the 

coastal plain, however, had indefinite horizons or no 

horizons and are termed azonal soils. Soils at two sites in 

the low-rate area were azonal lithosols, and soils at five 

sample sites in the high-rate area and two in the low-rate 

area were regosols. The lithosols were sampled by digging to bedrock or to a zone so stony that further 

digging was impractical, and the depth of the holes in 

the regosols was arbitrarily set at 2 feet. These two types 

of soil were sampled just below the surface, midway 

down the hole, and at the bottom of the hole; and the 

samples were, for convenience, desigated A, B, and C 

horizons, respectively.
CIO STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

In order to obtain some measure of the homogeneity 

of soils at a site, two additional soil-sample holes were 

dug and the three soil horizons were sampled at each of 

five tree-sample sites in each of the different death rate 

areas. These additional sample holes were randomly 

located within a 30-foot radius of the initial soil-sample 

hole. The 60 additional samples, when added to the 30 

samples of the initial sample holes at the sites, provided 

90 samples for the study of soil homogeneity. The results of this study are given in table 4.

The garden soils were sampled by taking the required 

amount from soil that was 1-2 inches below the surface. 

These soils were well pulverized when sampled and had 

been thoroughly mixed by cultivation practices that 

had extended over many years, therefore only the 

"plow zone" was sampled. No attempt was made to 

record past or present fertilizing practices; questioning 

the owners from place to place about fertilizing soon 

revealed that such information was either unknown, 

uncertain, or of doubtful accuracy in regard to kinds 

of fertilizers used, rates and frequency of application, 

and the years when the alleged applications were made.

Widespread use of insecticides, principally lead 

arsenate and paris green (arsenic trioxide and copper 

acetate), is known to have been prevalent in past decades, therefore heavy metal residues were expected to be 

found in garden soils. Analyses of these soils, however, 

did not reveal unusual concentrations of these metals.

The soil samples were air dried, then sifted through a 

200-mesh sieve and the 200 fraction used for chemical 

analysis. Some samples that had a large clay content 

were so hard when dry that it was necessary to grind 

them to powder in a ceramic mill before sieving.

PROCEDURES USED IN CHEMICAL ANALYSIS

The content of elements in plants that is reported 

was determined by analysis of the plant ash. The ash 

yield of the dry plant sample also is reported, therefore 

the element content of the dry plant can be computed. 

Contents of zinc and phosphorus were determined by 

colorimetric methods that were described by Ward, 

Lakin, Canney, and others (1963). Analyses for 

amounts of calcium were made by the EDTA titration 

method, and analyses for potassium by flame photometry. Quantities of the other elements were determined by semiquantitative spectrographic analysis 

(Myers, and others, 1961) after the ash of plant samples had been diluted with an equal weight of matrix 

composed of sodium silica (10 percent Na). These values were reported in geometric brackets having the 

boundaries 1.2, 0.83, 0.56, 0.38, 0.26, 0.18, 0.12, and so 

forth, percent; the brackets are identified by their 

respective geometric midpoints, such as 1.0, 0.7, 0.5, 0.3,

0.2, 0.15. Thus, a reported value of 0.3 percent, for 

example, identifies the bracket from 0.26 to 0.38 percent 

as the analyst's best estimate of the concentration. The 

precision of a reported value is approximately plus or 

minus one bracket at the 68-percent level of confidence 

and plus or minus two brackets at the 95-percent level.

Soil samples were analyzed by the same methods that 

were used for plants, except the pulverized soil was not 

burned to ash (most samples had a very low organic 

content) and a matrix was not added to the sample for 

spectrographic analysis. The chemical composition of 

soil samples was reported as parts per million or percent of the air-drv weight of the soil.

The limits of detection of the analytical methods that 

were used follow (table 3).

TABLE 3. Analytical limits of detection

[Values given are the lower limits, in percent, for the semiquantitative spectrographic 

method that was used, unless otherwise noted]

Element and chemical 

symbol

Detection 

limit

Element and chemical 

symbol

Detection 

limit

Aluminum (Al)_ --------

Barium (Ba)... ---------

Boron (B). ..............

Calcium (Ca)__ _-_--.--.

Cerium (Ce) ............

Chromium (Cr). --------

Cobalt (Co). ..-.-. ------

Copper (Cu)---_--------

Gallium(Ga)------.----

Iron (Fe)---------------

Lanthanum (La)-. ------

Lead (Pb). -----------

Magnesium (Mg). -------

Manganese (Mn) ........

0.001

.0002

.002

i.OOl

.015

.0001

.0003

.0001

.0005

.001

.003

.001

.005

.0001

Neodymium (Nd)_. _ ..

Nickel (NO.... -------

Niobium (Nb). ---------

Phosphorus (P)--- ------

Potassium (K). ---------

Scandium (Sc). ---------

Sodium (Na)..----------

Strontium (Sr)-.-----.--

Titanium (Ti). ---------

Vanadium (V).. ........

Ytterbium (Yb). .-.----.

Yttrium (Y). ..---....

Zinc (Zn).. ....------.--.

Zirconium (Zr).._ ...-.

0.007

.0003

.001

2 . 002 3.02

.0005

.05

.0005

.0002

.0007

.0001

.001

2 . 0025

.001

' Analyzed by EDTA titration method. 

2 Analyzed by colorimetric method, 

a Analyzed by flame photometry.

The values given in table 3 are approximate lower 

limits of determination. Some combinations of elements 

in a sample, however, affect these limits. Concentrations 

somewhat lower than these values may be detected in 

unusually favorable materials, whereas these limits of 

determination may not be attained in unfavorable materials. Upper limits in measuring the amounts of magnesium, were exceeded by a few plant samples; these 

analyses were reported as >10 percent.

METHODS OF STATISTICAL ANALYSIS

The objective of the statistical analysis of the data 

has been to examine differences between plant and soil 

geochemistry in the high- and low-death-rate areas. The 

statistical significance of the differences between the 

two estimated means for each element concentration in 

each sample media was determined by analysis of variance methods. Analysis of variance was also used in 

the estimation of total sampling and analytical error 

associated with an individual site at which the A, B, and 

C horizons of uncultivated soils were collected. Cor-
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA Gil

relation coefficients were computed to examine the covariation among the compositions of the various sampling media among the sampling sites in both the 

high- and low-death-rate areas.

Frequency distributions of most of the original 

chemical data, in units of weight percent, display high 

positive skewnesses and the variances of the distributions tend to be proportional to their respective means. 

Log transformation of the original data proved effective 

in correcting both these situations to a satisfactory 

degree. The frequency distributions of the logs of the 

original data tend to be normal ; the distributions of the 

original data tend to be lognormal. Log transformation 

also overcomes some effects of the geometric brackets in 

which spectrographic analyses are reported (Miesch, 

1967b, p. B5).

The geometric means were estimated by use of the 

antilog of the arithmetic mean of the logs. This is the 

appropriate measure of central tendency for a lognormal distribution and provides a "typical" or 

"characteristic" value for the element in the various 

sample media. A measure of variation is given by the 

geometric deviation, which is the antilog of the standard deviation of the logs. About two-thirds of the area 

under the lognormal distribution curve lies in the range 

GM -s- GD to GM X GD, where GM is the geometric 

mean and GD is the geometric deviation. The confidence interval about the geometric mean, the geometric error ( GE} , can be estimated from

GE=lQ(t IOBOD/V^

where t is Student's t and N is the number of values on 

which the geometric mean is based. Where t is selected at the 0.05 level of probability, the population 

geometric mean has the expected range GM -=- GE to 

GM X GE, with 95-percent confidence.

Many of the elements studied were not detected in 

part of the samples from each media. The elements 

are presumably present in the media, but in concentrations below the sensitivities of the analytical methods 

used. Means and variances of the log concentrations, 

in these cases, were estimated by use of Cohen's (1961, 

p. 535) technique for type I censored distributions. 

The estimators are:

jl=x \(x XQ) and

where /} and a- 2 are estimates of the population mean 

log and variance of the logs, respectively, x and sz are 

the mean and variance of the logs of the concentration values above the analytical sensitivities, x0 is the 

log of the sensitivity, and X is taken from table 2 of

Cohen (1961, p. 538). The estimated geometric mean 

is

and the geometric deviation is

Estimated geometric means and geometric deviations 

are given in tables 5-7. Where the element was not 

detected in some of the samples analyzed, as indicated 

on the tables, the estimates were derived by Cohen's 

technique.

The statistical significance of differences between 

mean concentrations of constituents in various media in 

the high- and low-death-rate areas was estimated by 

analysis of variance methods ; results are given in tables 

5-7. Differences between means estimated from highly 

censored data were not tested; the required statistical 

tests are not available. Where the censored part of the 

distribution was small, the unknown values were assigned to a semiquantitative spectrographic class immediately below the limit of sensitivity of the analytical 

method. The principal justification for replacing the 

unknown values is that the final answers are nearly 

independent of any reasonable values that may be used. 

The validity of analysis of variance results (tables 5-Y) 

rests on three principal assumptions: (1) the sampling 

and analysis have been unbiased, or biases which may 

be present tend to be constant among sampling sites 

(Miesch, 1967a, p. A14), (2) the frequency distributions of the data are drawn from corresponding lognormal population distributions, and (3) the geometric 

deviations of the population frequency distributions 

are equal. The correctness of the first of these assumptions can only be inferred from the nature of the sampling techniques and methods of analysis, already 

described. The other two assumptions are only approximately correct, as inferred from tests for normality and 

variance homogeneity; but the observed departures of 

the respective properties from the ideal conditions are 

not sufficient to seriously invalidate the results.

It is doubtful that any two areas, even areas in proximity, contain exactly the same concentrations of any 

particular element or other constituent in any particular media. The analysis of variance, therefore, is an attempt to demonstrate the existence of differences we can 

be quite sure are present without the analysis, and failure of the tests to demonstrate a difference merely indicates that the test lacks sufficient power (the power could 

be increased by taking more samples). The purpose 

of the analysis of variance, therefore, is not to demonstrate the existence of differences in composition between 

the two areas, but to find those differences which appear
C12 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

to be large when compared with the variation within 

each of the two areas.

The computational procedures used in the analysis of 

variance followed those described by Anderson and 

Bancroft (1952, p. 327-330) for designs containing unqual numbers in subclasses.

Estimates of experimental error in the data pertaining to uncultivated soils were obtained from replicate 

sampling at 10 sites, five in the high-death-rate area 

and five in the low-death-rate area. Three sample 

holes, at random locations as much as 60 feet apart, 

were dug at each of the 10 sites, and samples were 

taken from each of the A, B, and C soil horizons. A 

total of 90 samples were used. The statistical model 

employed was

where Xijk is the log concentration of an element in 

the kth sample (1<&<3) from the jth site (l<j<5) 

in the iih area (l<i<2), from either the A, B, or C 

horizon; /j, is the grand mean log concentration of the 

element in the A, B, or C horizon at all sites, o^ is the 

deviation of the high- or low-death-rate area mean 

from the grand mean, (3 i} is the deviation of the site 

mean from the area mean, and y {jk is the deviation of 

the log analytical value for a single hole from the 

mean for the site. The validity of the model depends 

on the absence of variable bias in sampling and analysis 

(Miesch, 1967a, p. A14). Estimates of the variance 

components for a, ft, and 7 were derived according to

Source

Between areas. 

Between sites 

Between holes.

Degrees of Mean square is 

freedom estimate of

8

20

Estimates of the individual components, a^, o%, and 

<4 are given in table 4. In general, the variance between the high- and low-death-rate areas (a«) is 

sufficiently large in comparison with variance components between sites and between samples that no 

difficulties are foreseen in identifying compositional 

differences between areas. With 30 sites per area and 

one sample per site, the within-area variance of the 

mean log for aluminum in the A horizon, for example 

is

0.021 +

0.016

30 = 0.0012.

This value is a measure of the total error of the mean 

log aluminum content for an area and is satisfactorily 

low as compared with the variance between areas, 

0.246 (table 4).

TABLE 4. Components of logarithmic variance between samples, 

sites, and areas where uncultivated soils were sampled in the highand low-death-rate areas

[Numbers in italic indicate that the variance is significant at the 95-percent level 

of confidence]

Component of logarithmic variance

Between samples (<r.y 2) Between sample sites Between areas (<ra 2) 

Element (<r/3 2)

Soil horizons 

ABCABCABC

AL........ 0.016 0.013

Ba. 

Ca.. 

Or.. 

Cu. 

Fe..

Mg. 

Mn. 

Nb. 

P 

TL. 

V...

Yb. 

Zr..

.021

.023

.018

.020

.021

.018

.030

.028

.020

.044

.015

.022

.036

.041

.037

.041

.007

.044

.027

.025

.042

.022

.020

.034

.049

.009

.011

.064

.041

.023

0.031

.014

.017

.028

.042

.020

.014

.062

.022

.034

.047

.010

.033

.020

.025

.042

0.021

.017

.013

.037

.073

.077

.001

.010

.058

.053

.018

0.038 0.095

.025 .045

.019 .010

.031

.035

.117

.078

.063

.001

.033

.017

.022

.014

.016

.059

.091

.037

.118

.059

0

.047

.017

0

0.246

.125

.048

.165

.143

.196

.819

.593

.060

.001

.067

0

. 0^8 .252

.114

.095

0.340

.106

.189

.307

.707

.701

.233

.003

.081

.013

.266

0

.013

.009

O.S18 

.091 

.094 

.114 

.139 

.SOI 

.702 

.519 

.190 

.004 

.006 

.003 

.181

0

0 

.026

The variance among sample sites within the high- and 

low-death-rate areas is generally similar to the variance 

within sites (table 4). This appears to be true for all 

chemical elements in all three soil horizons. Consequently, if further studies were undertaken with an 

objective that depended on distinguishing among the 

sites within either area, it would be necessary to collect 

considerably more than one sample at each site.

For example, in order to distinguish between two sites 

with respect to aluminum in the A soil horizon (table 

4), it would be necessary to collect a sufficient number 

of samples, n, within each site so that the observed F 

ratio, estimated by

(0.016)+7i(0.021) 

(0.016)

would exceed the critical F at a stated level of probability for 1 and 2(n 1) degrees of freedom. In this 

case, for the 0.05 level of probability, n must equal or 

exceed 4; at least four samples from the A horizon at 

each sample site would be required.

Comparison of mean element concentrations (tables 

5-7) for various plant and soil media in the high- and 

low-death-rate areas serves to identify covariation between plant and soil compositions on a broad scale. For 

example, the generally lower concentrations of many 

elements in both soils and trees of the high-death-rate 

area (tables 6,7), compared with those of the low-deathrate area, points to a broad-scale covariation between 

tree and soil chemistry. Such covariation, however, may 

or may not be present on a smaller scale within either 

of the two areas. Covariation between soil and plant 

compositions within both the high- and low-death-rate 

areas was examined by means of product-moment cor-
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C13

relation coefficients (tables 8-11). Correlation coefficients were also used to examine covariation among soil 

horizons (table 12), and between the stems and leaves 

of trees (table 13) within each of the two areas.

The correlation coefficients are based on logarithms of 

the element concentrations. In cases where the element 

was not detected in either the plant or the soil (or the 

stem or the leaf) at a sampling site, that site was not 

represented in the data used. Therefore, the bivariate 

frequency distributions on which the correlation coefficients are based are censored at either or both the leftmost or the lowermost extremes. The degree of censoring 

is indicated by the number of sites in which the element 

was not detected in either or both sampling media 

(tables 8-13).

In cases where the element was detected in both 

sampling media at all sampling sites (that is, N=Q on 

tables 8-13), the bivariate frequency distributions of the 

logarithmic concentrations are uncensored and approximately normal. The statistical significance of the correlation coefficients, in these cases, may be determined 

from widely available tables of critical values of r. However, where the element was not detected in either or 

both sampling media at one or more sites (for example, 

NT*® on tables 8-13), the statistical significance of the 

correlation coefficient is indeterminable, and the coefficient must be regarded only as a relative index of 

covariation.

RESULTS OF ANALYSES 

COMPOSITIONS OF VEGETABLES AND GARDEN SOILS

The contents of certain elements in samples of vegetables and garden soils from the two death-rate areas, 

expressed as geometric means (in percent), and the 

variations in contents expressed by geometric deviations 

are given in table 5. The ash content of vegetables also 

is provided to permit converting the amounts of elements in vegetable ashes into amounts in the oven-dry 

vegetables. The weight of samples before dehydration 

(wet weight) was not recorded; therefore, the element 

content of "fresh" vegetables cannot be computed from 

these data.

COMPOSITIONS OF TKEES AND UNCULTIVATED SOILS

The contents of certain elements in samples of tree 

stems and leaves from the two death-rate areas, expressed as geometric means (in percent), and the variations in contents expressed by geometric deviations are 

given in table 6. The ash contents of stems and leaves 

are also provided to permit converting the amounts of 

elements in the ashes into amounts in the oven-dry 

stems and leaves.

368-640 O 70 3

Data in table 6 show that leaves, when burned, yield 

about twice as much ash as do stems. This difference 

in yield is believed not to result from contamination of 

leaves by dust, but to be caused by the difference in 

element content of primary and secondary growth 

products. Leaves have only primary growth (originating in primary meristem); stems have, in addition, 

secondary growth (originating in the cambium). 

Secondary growth produces an increase in "dry weight" 

as a result of the synthesis of organic compounds (lignin, among others) without a corresponding increase in 

amounts of the elements that constitute ash. Therefore, 

if equal weights of dried stems and leaves are burned 

the organic compounds are oxidized, and a greater 

weight of ash remains from the burned leaves.

An examination of the element content in the ash of 

tree stems and leaves reveals the following tendencies 

in element concentration:

Concentration greater in the stems barium, calcium, copper (for several species), lead, and 

strontium.

Concentration greater in the leave? aluminum, 

iron, magnesium, potassium, titanium, ytterbium, 

and zirconium.

Apparently equal or approximately equal concentrations in stems and leaves boron, chromium, 

copper (for most species), manganese, nickel 

(variable with species), and phosphorus. 

The element contents of uncultivated soils from the 

two death-rate areas are given in table 7. The contents 

(geometric means) of elements are printed in italic if 

the differences in content between the two areas are 

significant. If the differences in the content of an element are significant in one soil horizon, they are also 

significant in the other two horizons, except for ytterbium in which only the A horizon has this difference. 

In garden soils (table 5) and in uncultivated soils 

(table 7) the same elements exist but in concentrations 

that are significantly different in the two death-rate 

areas. This fact suggests that cultivation practices over 

a period of years have not greatly altered the contents 

of many elements in garden soils.

CORRESPONDENCE BETWEEN THE COMPOSITIONS 

OF PLANTS AND SOILS

The correspondence between amounts of chemical 

elements in plants and those in soils in the areas studied 

can be examined, with the data available, on two scales. 

Correlation on a broad statewide scale may be examined 

by comparing the average plant and soil compositions 

for the high- and low-death-rate areas (tables 5-7). 

Correlation on a more detailed scale, between plant and
C14 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 5. Ash contents of vegetables and element contents of vegetable ashes and garden

[GM, geometric mean (in percent); GD geometric deviation; N, number of samples in which the element was not detected; ._ , insufBcient data; geometric means are in

John B. McHugh, Harriet Neiman, A. L. Sutton, Jr.

Kinds, localities,

Element, o:

Ash

Al

B. .....................

Ba--.- . - 

Ca.----.... ............

Ce... --------------

Co. -- --

Cr. ._.-.-_ -- --_

Cu - - - 

Fe_ -- . -..-...

O&..... ................

K... ....................

IA.. ...................

Mg.. .. ....

Mn.. .- -.-.

Mo - .-----_

Nb------. -- ...

Ni... ... ........ __

P. - ... .- .

Pb -- ...

Sc.. ....... ............

81.. .................

TL.... .................

V. ..................

^f...... ...............

Yl>. ...................

Za... ...................

Zc. ....................

B lackeyed peas

High-rate area 

29 samples

GM

................. 5.9

- .-- .059

 -.-.--..... .022

................. .013

-._-._._....... 6.6

................. .0096

- ... --. .11

...-. ... - 31

_- .-. .. 5.0

- -..-.---... .081

................. .00011

-..... . - .0018

---..-... -... 7.0

-.- -. .018

.- --.-...-. .0037

.-.- ..--.. .075

GD

1.26 

2.03 

1.54 

2.06 

1.31

1.37 

1.43

1.09

1.62 

1.64 

9.72

1.60 

1.30

1.81 

2.53

1.27

N

0 

0 

0 

0 

0 

29

28 ..

17 ..

0 

0 

29 _.

0 

29 ..

0 

0

21 ..

29 ._

0 

0 

25 ._

29 -.

0 

0 

28 ..

28 ..

29 ..

0

27 ..

Low-rate area 

4 samples

GM

5.2 

.052 

.014 

.0077 

4.7

.010 

.11

33

5.2 

.048

.0013 

7.8

.013 

.0018

.065

GD

1.09 

1.64 

1.22 

1.20 

1.29

1.00 

1.55

1.05

1.49 

1.42

2.74 

1.21

1.40 

2.96

1.09

N

0 

0 

0 

0 

0 

4

4

3 

0 

0 

4

0 

4

0 

0 

4 

4

1 

0

4

0 

0 

4 

4

0 

4

and numbers of samples

Cabbage

High-rate area 

28 samples

GM

19.0 

.// 

.0083 

.032 

16

.00022 

.0022 

.071

21

2.7 

.045 

.00012

. 0000181

2.1

.062 

.0085 

.0014

.034 

. 0000463

GD

1.41 

1.90 

1.72 

2.95 

1.38

1.66 

1.57 

1.46

1.33

1.90 

2.40 

6.18

1.46 

1.63

2.34 

2.37 

1.23

2.57 

5.4

N

0 

0 

1

0 

0

28

28

8 

0 

0

28

0

28

0 

0 

21

28

24 

0

27

28

0 

0 

25 

25 

?6

0 

22

Low-rate area 

30 samples

GM

21.0 

.89 

.0058 

.045 

SO

.00057 

.0021 

.19

18

2.2 

.040 

.000077

.00030

1.2

.088 

.026

.0000421

.081 

.00035

GD

1.16 

2.45 

2.29 

1.67 

1.19

2.61 

2.04 

2.13

1.24

1.68 

2.26 

7.41

1.87 

1.38

1.89 

2.82

1.2

2.39 

6.3

N

0 

0 

5 

0 

0 

30

29

4

0 

0 

30

0

?7

0 

0 

24 

30

25 

0 

29 

30

0 

0

25

26

?8

0

Corn

High-rate area 

29 samples

GM

4.4 

.066 

.0055 

.0054 

1.8

.010 

.086

35

3.7

.035 

.00025

.00027 

11 

.00071

.0052 

.0020

.084

GD

1.47 

2.03 

1.78 

2.37 

1.44

1.35 

1.57

1.09

1.66 

1.64 

3.69

3.22 

1.19 

3.11

1.75 

5.00

1.44

N

0 

0 

3

0 

0

29

TO

20 

0 

0 

29

0

TO

0 

0 

10

?9

15 

0 

23

?9

0 

3

TO

TO

TO

0

?8

Low-rate area 

30 samples

GM

3.7 

.068 

.0037 

.0047 

1.7

.00014 

.0094 

.099

36

4.0 

.003

.00058 

10

.0050 

.0021

.085

GD

1.55 

1.99 

2.25 

2.12 

1.51

1.83 

1.37 

1.65

1.07

1.41

1.87

1.51 

1.26

1.95 

3.79

1.38

N

0 

0 

8 

0 

0 

30 

30 

20 

0 

0 

30 

0 

30 

0 

0 

29 

30 

14 

0 

29 

30 

0 

1 

30 

30 

30 

0 

30

soil compositions within the high- and low-death-rate 

areas, has been examined by means of correlation coefficients (tables 8-11).

The concentration of some elements in 'soil (in an 

available form) is commonly assumed to determine the

amount that the plant will absorb, unless the element is 

present in extremely large, or toxic, quantities or as 

toxic compounds. The major and minor essential elements obviously must be absorbed in quantities sufficient 

for metabolism of the plant, regardless of their relative
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C15

soils from two areas in Georgia that have different cardiovascular mortality rates

italic where they are significantly different for the high- and low-death-rate areas at the 95-percent level of confidence. Analysts: John C. Hamilton, Thelma F. Harms, 

Barbara Tobin, and James H. Turner]

Kinds, localities, and numbers of samples Continued

Green beans

High-rate area 

30 samples

GM

8.4 

.087 

.016 

.017 

5.3

.00024

.0085 

.099

33

3.6 

.037 

.00047

.0015 

4.9

.021 

.0073

.053 

.0000313

GD

1.34 

2.18 

1.53 

2.73 

1.39

2.79

1.47 

1.36

1.10

1.42 

1.88 

5.20

2.27 

1.30

1.80 

2.69

1.36 

3.3

N

0 

0 

0 

0 

0 

30

24 

11

0 

0 

30

0 

30

0 

0 

15 

30

2 

0 

9R

30

0 

0

W

9S

30

0 

25

Low-rate area 

30 samples

GM

6.8 

.15 

.014 

.052 

6.5

.00062

.Oil 

 U

33

4.3 

.034 

.00023

.0017 

5.2

.029 

.0070

.052

GD

1.14 

2.28 

1.30 

2.04 

1.31

3.31

1.40 

1.96

1.08

1.49 

1.70 

5.60

2.37 

1.25

1.75 

2.59

1.23

N

0 

0 

0 

0 

0 

30

15 

10 

0 

0 

30

0

29

0 

0 

19 

30

2 

0

28

30

0 

0 

919

30

30

0 

30

Lima beans

High-rate area 

30 samples

GM

5.5 

.032 

.0094 

.0/0 

3.0

.000042 

.0093 

.11

35

3.4 

.032 

.00096

.0019 

6.7

.0088 

.00083

.060

GD

1.13 

2.43 

1.54 

2.14

1.32

3.53 

1.29 

1.27

1.05

1.53 

1.68 

4.88

1.93 

1.25

1.63 

3.93

1.18

N

0 

0 

0 

0 

0 

30

27 

9fi

0 

0 

30

0 

30

0 

0 

10 

30

0 

0

29

30

0 

4 

30

30

30

0 

30

Low-rate area 

15 samples

GM

6.7 

.14 

.0070 

.019 

3.7

.00046

.0094 

.16

S4

2.8 

.038 

.00051

.0021

4.7

.014 

.0027

.039

GD

1.18 

3.11

1.73 

2.67 

1.63

1.63

1.34

2.15

1.08

1.15 

1.61 

3.29

2.17 

1.28

2.28 

8.00

1.47

N

0 

0 

0 

0 

0 

15

10

9 

0 

0

15

0 

15

0 

0

7

15

0 

0 

14

15

0 

1

14

15

15

0 

15

Tomatoes

High-rate area 

30 samples

GM

11.0 

.067 

.0056 

.0060 

1.7

.00024 

.0079 

.078

38

1.7

.017

.00011 

4.0 

.00056

.0071 

.0032

.029

GD

1.40 

2.96 

1.73 

2.43 

1.44

2.54 

1.48 

2.21

1.07

1.41 

1.94

4.9 

1.30 

6.46

1.96 

4.31

1.40

N

0 

0 

3 

0 

0 

919

30

11

0 

0 

30

0

919

0 

0 

97

30

m

0. ??

30

1 

1 

27

919

30

0

9Q

Low-rate area 

30 samples

GM

9.8 

.044

.0038 

.0038 

1.5

.0086 

.053

40

1.5 

.0/0

3.0

.0069 

.00056

.mi

GD

1.20 

2.60 

1.88 

1.80 

1.27

1.71 

1.56

1.08

1.38 

1.49

1.22

2.00 

4.25

1.39

N

0 ..

0 

6 

0 

0 

30 

29 

25 

0 

0 

30

0 

30 

0 

0 

30

30 

30 

0 

30 

30 

0 

6 

30 

30 

30 

0

30

Garden soils

High-rate area 

30 samples

GM

0.90 

.0025 

.0063 

.080 

.0036 

.00013 

.00/5 

.00099 

.55

.041 

.0018 

.027 

.0099

.00/3 

.00018 

.0/7 

.00026 

.00028 

.00036 

.19 

.0020 

.0022 

.00027

.081

GD

1.88 

1.91 

1.42 

2.16 

3.37 

2.68 

2.00 

1.85 

2.59

2.30 

2.86 

1.84 

2.14

1.34 

4.02 

2.10 

2.77 

1.65 

2.35 

1.36 

1.92 

1.99 

1.76

1.59

N

0 

15 

0 

0 

?,5

26 

0 

0 

0 

22 

0 

19 

0 

0 

30

5 

19 

0 

26 

22 

25 

0 

0 

1 

0 

21 

0

Low-rate area 

30 samples

GM

4.6 

.0031

.025 

.17

.00099 

.0048 

.0039 

2.0 

.0020 

.92 

.0033 

.24 

.041

.0016 

.0018 

.043 

.0026 

.00090 

.0033 

.32 

.0065 

.0025 

.00028 

.0064 

.0/8

GD

1.70 

2.47 

1.52 

2.19

1.68 

1.62 

2.01 

1.54 

1.78 

1.91 

2.14 

1.95 

1.84

1.52 

1.70 

1.73 

2.31 

1.35 

2.21 

1.41 

1.38 

1.44 

1.45 

1.82 

1.48

N

0 

13 

0 

0 

25 

2 

0 

0 

0 

0 

0 

12 

0 

0 

30 

5 

0 

0 

2 

0 

1 

0 

0 

0 

0 

0 

0

abundances in the soil, or the plant could not live. It is 

generally known, however, that many plants may absorb 

larger quantities of these elements than are required for 

metabolic processes, if large amounts are available in 

the soil the so-called luxury consumption of elements

by plants. Controlling factors in the absorption of the 

nonnutritive elements are poorly understood. A discussion of the complex chemical and physiological processes involved in the absorption of elements by plants 

is beyond the scope of this report. (See Sutcliffe, 1962.)
C16 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 6. Ash contents of trees and element contents of tree ashes from

GM, geometric mean (in percent); GD, geometric deviation; N, number of samples in which the element was not detected; ..--, insufficient data; geometric means are in

John B. McHugh, Harriet Neiman, A. L. Sutton, Jr.,

Element, or ash, 

and kind of 

sample

leaves...-. _____ 

Ash, stems...-...

leaves.... ____

Mn, stems______-

Mo, stems.. ______

leaves. _________

leaves __________

Ti, stems. ..... ..

Y, stems. ________

Zn, stems . _ ___

Kind, localities, and number of samples

Blackgum

High-rate area 

30 samples

GM

0.52 

.91 2.4

4.3 

.043 

.060 

.72

25'" 

17 

.012 

.029 

.00078 

.00064 

.024 

.013 

.14 

.18 

11 

16

5.7 

>10 

.84 

.93

.0031 

.0062 

1.3 

1.7 

.025 

.0057 

.19 

.093 

.015 

.020 

.00069

.00017 

.000090 

. 0000059 

. 0000090 

.091 

.026 

.00021 

.00097

GD

1.69 

2.12 

1.26 

1.25 

1.57 

1.75 

2.18 

2.54 

1.14 

1.21 

3.54 

5.83 

2.37 

2.13 

1.88 

1.90 

1.69 

1.84 

1.30 

1.23

1.45

2.69 

2.53

2.24 

3.31 

1.37 

1.33

2.88 

2.01 

1.93 

1.72 

1.81 

2.22 

2.24

7.35 

9.71 

10.37 

9.71 

1.65 

1.39 

7.22 

4.11

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

2 

3 

0 

1 

0 

0 

0 

0 

0 

0 

29

30

0

0 

0

29

Of)

1 

1 

0 

0 

1 

1 

0 

0 

0 

0 

23 

28

24 

25 

26 

25 

0 

0 

23 

15

Low-rate area 

30 samples

GM

0.63 

1.1 

8.8 

5.9 

.036 

.041 

.98 

.41 

26 

16 

.019 

.040 

.00079 

.0010 

.027 

.010 

.19 

.26 

11 

19

5.9 

8.6 

.95 

.96

.0060 

.012 

1.8 

1.6 

.048 

.0096 

.35 

.19 

.014 

.024 

.00070 

.00058

.00010

.097 

.027 

.00010 

.00049

GD

1.41 

1.58 

1.21 

1.18 

1.40 

1.50 

1.67 

1.73 

1.14 

1.26 

6.14 

7.67 

1.70 

2.00 

1.80 

1.37 

2.33 

2.47 

1.31 

1.25

1.33 

1.27 

1.86 

2.11

2.91 

3.20 

1.21 

1.28 

2.34 

2.56 

2.14 

1.94 

1.81 

2.23 

1.98 

3,80

6.55

1.47 

1.37 

6.55 

7.08

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

3 

3 

0 

0 

0 

0 

0 

0 

0 

0

0 

0 

0 

0 

30

30

1 

1 

0 

0 

0 

0 

0 

0 

0 

0 

24 

"3

28 

26 

%

35

0 

0 

26 

19

Oak

High-rate area 

30 samples

GM

0.15 

.31 

3.1 

3.0 

.028 

.058 

.36 

. 22 

31 

20

.00039 

.00053 

.Oil 

.015 

.085 

.17 

7.3 

15

3.4 

7.0 

.83 

1.4

.0011 

.0017 

.96 

2.2 

.0095 

.0070 

.15 

.082 

.0091 

.024 

.00046

.00021 

.00038

.034 

.044 

.00013 

.00086

GD

1.66 

1.70 

1.32 

1.19 

1.51 

1.42 

1.89 

2.04 

1.11 

1.11

1.58 

1.67 

1.57 

1.44 

1.32 

1.63 

1.52 

1.19

1.60 

1.27 

1.92 

1.93

1.72 

1.84 

1.70 

1.21 

2.40 

2.81 

1.69 

1.71 

1.63 

1.62 

2.35

5.61 

7.06

1.53 

1.33 

6.70 

3.97

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

28 

28 

1 

0 

0 

0 

0 

0 

0 

0 

28 

27 

0 

0 

0 

0 

30

30

0 

1 

0 

0

2 

2

0 

0 

0 

0 

26 

27 

24 

20 

29 

27 

0 

0 

25 

16

Low-rate area 

30 samples

GM

O.S8 

.73 

2.5 

3.3 

.026 

.044 

.42 

.19 

87 

15 

.00067 

.00050 

.00067 

.0011 

.017 

.017 

.19 

.38 

12 

18 

.0022 

.0018 

3.3 

5.1 

1.0 

1.3

.00/8 

.0034 

1.5 

2.2 

.020 

.016

.n

.P96 

.013 

.040

.00061 

.00039 

.0014 

.0000088 

.000067 

.053 

.056 

.000050 

.00075

GD

1.98 

1.76 

1.30 

1.25 

1.51 

1.54 

1.87 

1.97 

1.22 

1.35 

2.38 

2.59 

1.82 

1.81 

1.41 

1.34 

1.91 

1.89 

1.38 

1.17 

4.41 

3.86 

1.47 

1.53 

1.89 

1.76

1.79 

2.29 

1.47 

1.27 

2.90 

2.40 

1.72 

1.66 

2.13 

1.93

2.99 

4.87 

2.89 

7.30 

3.37 

1.74 

1.32 

11.97 

6.66

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

14 

17 

1 

0 

0 

0 

0 

0 

0 

0 

17 

19 

0 

0 

0 

0 

30

30

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

27 

22 

21 

11 

26 

18 

0 

0 

26 

17

Persimmon

High-rate area 

30 samples

GM

0.17 

.24 

3.1 

6.0 

.032 

.045 

.25 

.097 

23 

15

.00040 

.00034 

.023 

.0070 

.10 

.13 

16 

21 

. 00010 

.00024 

5.3 

7.3 

.72 

.89

.0027 

.0018 

1.5 

1.4 

.011 

.0024 

.11 

.054 

.0096 

.013 

.00046

.00010 

.00014 

.0000084 

. 000012 

.079 

.017 

.00024 

.00027

GD

2.07 

2.50 

1.23 

1.27 

1.53 

1.66 

2.29 

2.09 

1.24 

1.55

1.81 

1.79 

2.00 

1.52 

1.46 

1.56 

1.31 

1.24 

18.02 

11.27 

1.43 

1.67 

1.99 

2.35

1.88 

2.25 

1.60 

1.28 

2.90 

4.13 

1.91 

2.03 

2.09 

2.27 

2.35

19.05 

18.93 

10.36 

14.43 

1.46 

1.58 

4.61 

4.91

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

2437

2 

3

0 

0 

0 

0 

0 

0 

26 

25 

0 

0 

0 

0 

37

39

0 

0 

0 

0

1

8 

0 

0 

0 

0 

26 

29 

23 

22 

25 

23 

0 

0 

24 

23

Low-rate area 

30 samples

GM

0.24 

.32 

3.0 

7.3 

.028 

.036 

.19 

.071 

20 

16 

.00022

.00051 

.00050 

.025 

.0064 

.15 

.19 

19

OQ

" .00042 

.0022 

4-4 

5.5 

.62 

.80

.0043 

.0019 

2.0 

1.6 

.015 

.0068 

.11 

.062 

.010 

.015 

.00060 

.00040 

.000074 

.00054

.11 

.020

GD

1.93 

2.04 

1.18 

1.27 

1.71 

1.80 

2.40 

2.57 

1.28 

1.30 

3.63

2.57 

2.02 

1.59 

1.49 

2.34 

2.18 

1.25 

1.19 

6.46 

3.03 

1.37 

1.43 

1.86 

1.97

2.20 

1.87 

1.51 

1.36 

3.85 

2.59 

1.96 

1.98 

2.18 

1.99 

2.07 

2.65 

8.55 

3.38

1.61 

1.32

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

23 

30

3 

1

0 

0 

0 

0 

0 

0 

25 

18 

0 

0 

0 

0 

38

30

0

Q

0 

0

] 

] 

c 

o 

r 

c

2f

26 

26 

20

39

37

0 

0

V

28

Red maple

High-rate area 

30 samples

GM

0.14 

.19 

2.9 

4.9 

.037 

.042 

.35 

.14 

24 

17

.00039 

.0004/ 

.015 

.014 

.094 

.17 

11 

/*

2.5 

5.1 

.68 

.82

.00075 

.00040 

1.4 

1.8 

.018 

.004- 

.15 

.068 

.0086 

.0/4 

.00046

.048 

.045

.00065

GD

1.67 

2.44 

1.22 

1.24 

1.36 

1.73 

2.82 

2.73 

1.19 

1.21

2.15 

1.67 

1.27 

1.86 

1.47 

1.96 

1.51 

1.26

1.50 

1.56 

1.80 

2.63

2.26 

3.15 

1.51 

1.30 

2.59 

2.92 

1.87 

1.97 

1.81 

2.33 

2.35

1.40 

1.41

4.19

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

39

30

3

2 

0 

0 

0 

0 

0 

0 

30

30

0 

0 

0 

0

39

39

12 

0 

0 

1 

4 

0 

0 

0 

0 

26 

38

39

37

38

38

0 

0

37

18

Low-rate area 

30 samples

GM

0.17 

.37 

2.7 

4.8 

.035 

.036 

.36 

.13 

25 

16

.00046 

.00060 

.015 

.015 

.14 

.88 

12 

15

2.3

4.9 

.68 

.67

.00086 

.00050 

1.6 

*./ 

.083 

.010 

.18 

.077 

.0093 

.081

.069 

.057

GD

1.63 

1.92 

1.24 

1.20 

1.34 

1.67 

2.17 

2.02 

1.20 

1.26

1.77 

1.80 

1.51 

1.45 

1.59 

1.89 

1.44 

1.31

1.50 

1.45 

1.92 

2.37

2.22 

3.13 

1.44 

1.26 

3.13 

2.21 

1.91 

2.04 

1.85 

1.84

1.30 

1.29

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

30 

30 

1 

0 

0 

0 

0 

0 

0 

0 

30 

30 

0 

0 

0 

0 

29 

30 

3 

10 

0 

0 

0 

0 

0 

0 

0 

0 

29 

28 

29 

30 

30 

30 

0 

0 

29 

27
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C17

two areas in Georgia that have different cardiovascular mortality rates

italic where they are significantly different for the high- and low-death-rate areas at the 95-percent level of confidence. Analysts: John C. Hamilton, Thelma F. Harms, 

Barbara Tobin, and James H. Turner]

Kind, localities, and number of samples Continued

Sassafras

High-rate area 

17 samples

GM

0.39 

.43 

1.9 

4.7 

.032 

.030 

.30 

.080 

21 

19

.0010 

.00076 

.016 

.014 

.19 

.22 

19 

19

3.2 

6.0 

.21 

.27 

.00016

.0012 

.0014 

0.0 

2.3 

.021 

.0083 

.18 

.11 

.032 

.030 

.0015 

.00070

.016 

.055 

.00063 

.00064

GD

2.42 

2.26 

1.31 

1.21 

1.70 

1.51 

2.26 

1.99 

1.35 

1.25

1.99 

1.78 

2.63 

2.21 

2.27 

2.35 

1.28 

1.27

1.69 

1.51 

2.07 

2.19 

3.87

1.55 

1.70 

1.31 

1.30 

2.37 

1.66 

2.30 

2.33 

2. « 

2.17 

1.83 

2.95

1.94 

1.65 

8.53 

5.92

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

17

17

1

0 

0 

0 

0 

0 

0 

0 

17

Ifi

0 

0 

0 

0 

14

0 

0 

0 

0 

0 

0 

0 

0 

0 

0

12

15

16

0 

0 

10 

10

Low-rate area 

27 samples

GM

0.37 

.63 

1.9 

5.7 

.025 

.015 

.26 

.071 

19 

15

.0010 

.00/3 

.017 

.012 

.25 

.35 

20 

23

3.0 

4.7 

.33 

.43 

.00013

.0014 

.0018 

2.5 

2. 2 

~014 

.00% 

.17 

.093 

.020 

.028 

.00074 

.00062

.13 

.046 

.00016 

.00010

GD

2.67 

2.04 

1.26 

1.13 

1.64 

1.46 

2.37 

1.76 

1.37 

1.27

2.47 

1.90 

1.34 

1.34 

3.21 

2.24 

1.33 

1.22

1.61 

1.46 

2.14 

1.89 

7.07

1.72 

1.80 

1.36 

1.28 

4.91 

2.28 

1.85 

1.91 

3.64 

2.42 

3.13 

2.83

1.68 

1.28 

15.21 

16.34

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

?6

?7

0 

0 

0 

0 

0 

0 

0 

0 

95

25"o

0 

0 

0 

21 >6

0 

0 

0

( 

6

0 

0 

0 

0 

18 

20 

27 

25 

?6

?,5

0 

0 

20 

21

Smooth sumac

High-rate area 

30 samples

GM

0.19 

.26 

3.6 

4.6 

.030 

.032 

.45 

.19 

25 

19

.00052 

.00050 

.016 

.0086 

.12 

.15 

14 

19

.00020 

2.9 

5.2 

.28 

 14

. 00074 

.00042 

1.7 

2.2 

.011 

.0057 

. 22 

.11 

.015 

.020

. 000090 

.00029

.000015

.074 

.036 

.00018 

.00062

GD

1.73 

1.86 

1.22 

1.20 

1.48 

1.54 

1.97 

1.84 

1.27 

1.21

1.67 

1.56 

1.56 

1.47 

1.66 

1.91 

1.53 

1.29

13.98 

1.53 

1.55 

2.14 

1.62

2.36 

3.15 

1.67 

1.35 

3.91 

2.29 

1.71 

1.59 

2.27 

2.01

9.71

9.20

8.42

1.43 

1.33

8.77 

5.00

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

29 

30

0 

0 

0 

0 

0 

0 

0 

0 

28 

25 

0 

0 

0 

0 

29

9R

11

0 

0

0 

0 

0 

0 

°7

°7

95

2 >8

94

0 

0 

2; 

18

Low-rate area 

30 samples

GM

0.23 

.51 

3.8 

4.8 

.023 

.025 

.32 

.13 

24 

18 

.00014

.00040 

.00072 

.016 

.0084 

.16 

.29 

16 

21 

.0012 

.0024 

2.3 

3.6 

.20 

.097

.00079 

. 00055 

1.9 

2.3 

.011 

.012 

.23 

.11 

.011 

.025

.00062

.00010

.078 

.037

.00013

GD

1.90 

2.12 

1.24 

1.32 

1.67 

1.84 

2.60 

2.42 

1.27 

1.22 

4.02

2.07 

1.93 

1.49 

1.44 

1.92 

2.25 

1.41 

1.25 

5.37 

4.59 

1.41 

1.49 

2.26 

1.85

3.23 

3.06 

1.41 

1.23 

3.0', 

2.25 

2.22 

2.28 

2.09 

2.47

2. 51

6.55

1.64 

1.44

14.62

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

25 

30

3 

1 

0 

0 

0 

0 

0 

0 

21 

17 

0 

0 

0 

0 

9<)

9f

( 

0 

1

0 

0 

0 

0 

0 

28

9Q

 C

26 *

27"o

0

?,8

2;

Sweetgum

High-rate area 

28 samples

GM

0.20 

.62 

4.8 

5.6 

.026 

.040 

.25 

.14 

26 

19 

.00020

.00045 

.00056 

.013 

.013 

.081 

.15 

6.1 

10 

. 00018

2.6 

7.0 

.41 

.96

.00/2 

.0029 

.71 

1.4 

.012 

. 0045 

.12 

.062 

.0077 

.012 

.00040

.000077 

.00011 

. 0000097

.000013 

.056 

.056

GD

1.48 

1.54 

1.32 

1.15 

1.38 

1.51 

1.99 

1.99 

1.17 

1.16 

3.72

1.60 

1.62 

2.20 

1.92 

1.48 

2.06 

1.89 

1.31 

12.00

1.46 

1.29 

1.99 

1.90

1.93 

2.07 

1.76 

1.42 

2.86 

2.47 

1.87 

1.80 

1.84 

1.94 

2. 4f

22.61 

21. 99 

16.49

11.37 

1.56 

1.41

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

22 

?6

0 

0 

0 

0 

0 

0 

0 

0 

24 

25 

0 

0 

0 

0 

9*

?8

1

0 

0 

0

] 

(

0 

0 

0 

25 

97

22 

21

92

22"o

0

°S

°5

Low-rate area 

27 samples

GM

0.37 

.55 

4.1 

5.6 

.019 

.028 

.28 

.13 

23 

16 

.00025

.00059 

.00091 

.015 

.013 

.// 

.19 

//

14 

.0022 

.0022 

3.1 

5.8 

.68 

1.3

.0030 

.0063 

1.8 

1.9 

.011 

.009/ 

.15 

.075 

.0069 

.014

.00027 

.0015 

.000020

. 00011 

.071 

.076

GD

1.77 

1.77 

1.37 

1.21 

1.39 

1.48 

2.03 

2.39 

1.31 

1.23 

1.92

1.73 

2.19 

1.46 

1.42 

2.00 

1.89 

2.10 

1.28 

3.04 

3.23 

1.63 

1.42 

1.74 

1.67

2.34 

2.11 

1.66 

1.33 

3.31 

2.07 

2.03 

1.98 

2.40 

2.09

6.06 

2.45 

5.08

3.51 

1.57 

1.35

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

24 

?7

0 

0 

0 

0 

0 

0 

0 

0 

16 

16 

0 

0 

0 

0 

?7

?7

0 

0 

0 

0 

1 

0 

0 

0 

0 

0 

27 

95

20

99

13

0 

0

95

Black cherry

High-rate area 

30 samples

GM

0.15 

.23 

2.0 

5.4 

.036 

.029 

.36 

.24 

26 

23 

.000055

.00050 

.00037 

.017 

.0077 

.15 

.14 

12 

14

. 00015 

4.8 

6.8 

.57 

.57

.00062 

.0014 

2.1 

2.0 

.021 

.0033 

.19 

.12 

.013 

.017 

.00030

.00019 

.00019

. 000013 

.13 

.022

.00020

GD

2.64 

1.90 

1.71 

1.22 

1.75 

1.43 

2.93 

2.59 

1.17 

1.16 

10.11

1.69 

1.83 

1.60 

1.50 

1.81 

1.75 

1.45 

1.37

12.79 

1.73 

1.73 

2.46 

2.44

2.94 

1.65 

1.60 

1.48 

2.71 

4.65 

1.68 

1.74 

1.82 

1.92 

3.45

8.09 

11.70

10.07 

1.59 

1.66

7.60

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

25 

30

1

(

0 

0 

0 

0 

0 

0 

27 

26 

0 

0 

0 

0 

?9?q

8 

0 

0 

0 

0

1 

0 

0 

0 

26 

?8

23

2' 

?7

24

0 

0

27">3

Low-rate area 

30 samples

GM

0.24 

.29 

2.3 

6.5 

.034 

.023 

.30 

.21 

25 

21 

.00037

.00061 

.0005/ 

.018 

.0069 

.19 

.2/ 

14 

17 

.0014 

.0017 

4.0 

6.7 

.56 

.37

.00058 

.0016 

, 2.3 

1.9 

.027 

.0058 

.24 

.16 

.011 

.014 

.00067

.00027 

.00043

. 000010 

.11 

.020

GD

2.26 

1.94 

1.30 

1.21 

1.48 

1.27 

3.12 

2.80 

1.23 

1.20 

2.39

1.99 

1.92 

1.52 

1.39 

2.52 

1.63 

1.51 

1.27 

5.14 

4.73 

1.49 

1.26 

2.27 

2.07

3.02 

2.24 

1.48 

1.36 

4.64 

2.40 

2.29 

2.11 

2.37 

1.95 

1.68

10.05 

5.91

6.55 

1.64 

1.38

N

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

21 

30 

2 

2 

0 

0 

0 

0 

0 

0 

20 

19 

0 

0 

0 

0 

30 

30 

9 

1 

0 

0

1 

1

0 

0 

0 

0 

26 

30 

21 

20 

27 

26 

0 

0 

30 

29
CIS STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 7. Element contents of uncultivated soils from two areas in Georgia that have different cardiovascular mortality rates

[GM, geometric mean (in percent); GD, geometric deviation; N, number of samples in which the element was not detected;... _. insufficient data; geometric means are in italic 

where they are significantly different for the high- and low-death-rate areas at the 95-percent level of confidence. Analysts: John C. Hamilton, Thelma F. Harms, John B. 

McHugh, Harriet Neiman, A. L. Sutton, Jr., Barbara Tobin, and James H. Turner]

Kinds, localities, and numbers of samples

Element

A horizon B horizon C horizon

High-rate area 

30 samples

Low-rate area 

30 samples

High-rate area 

30 samples

Low-rate area 

30 samples

High-rate area 

30 samples

Low-rate area 

30 samples

GM GD N GM GD N GM GD N GM GD N GM GD N GM GD N

Al. --------------

B. ...............

Ba. -------

Ca ... --.._...

Ce. ..............

Co...............

Cr.. ...... ..... -

Cu___ - __-_

Fe. ..... ......

Ga___ ___ -_

K -_--__-_

La..-.-- ......

Mg.- .... ....

Mn ... ..... ...

Na. ....... ...

Nb ... ...

Nd ..-. --.

Ni. ..............

p

Pb

Sc._. 

Sr...-_ - _-._

Ti...... ..........

V ...............

Yb --------

Zn.. .............

Zr... .............

-------- /./

------- .0018

---------- .0/0

------- .12

........... .00015

-.--..- .00//

-...- ..- .00057 if

........... .0015

------ .073

------ .0026

-------- .026

........... .013

........... .0029

--_-...- .0012

........... .00092

. ....... .000070

.___ . .0065

........... .00028

. ...-.. .00021

.... . .00057

-..- .. .17

........... .0015

........... .00025

........... .026

2.09

2.55

1.73

1.80

3.08

1 QQ

1.77

2.27

3.57

2.85

2.40

2.48

1.86

9.61

1.33

4.85

8.53

1 ca

4.24

2.64

2.73

1.94

2.14

9 ClA.

1.95

1.60

0

20

0

7

24

24

0

0

0

20

0

14

0

0

24

4

26 ..

22

0

23

22

19

0

4

1

0

23

0

4.4

.0022

.029

.31

.0079

.00098

.0041

.0026

2.1

.0017

/.*

.0034

.25

.032

.21

.0016

.0014

.020

.0021

.00086

.0030

.29

.0057

.0026

.00035

.0040

.020

1.97

3.08

1.85

1.44

1.58

1.74

1 70

1.72

1.68

2.32

1 QQ

1.73

2.19

1.64

2.82

1.43

2.10

2 09

1.83

1.47

1.50

1.58

1 CO

2.01

1.64

1 39

0

17

0

1

25

2

0

0

0

1

0

10

0

0

1 ...

3

28 ...

1

0

3 ...

1

0

0

0

0

1 ...

0

t t

.0020

.0086

.10

.0050

.00010

.0011

.00088

to

.00019

(YfO

.0024

.025

.0085

.0013

.0015

00 90

.00026

.00065

.18

.0016

.0020

.00025

fl&Q

1.86

1.85

1.68

1.51

2.19

3.19

1.81

1.77

2.04

2.31

2 84.

2.08

2.17

2.03

1.34

4.25

i on

2.06

1.61

1.64

1.90

1.77

1.66

- 1.62

0

20

0

9

26

26

0

0

0

20

0

16

0

0

27

3

28

20

27

21

21

0

4

0

0

27

0

5.7

.0025

.007

.33

.0058

.0010

0044

.0029

2.6

.0021

1 1

.0037

29

.028

.20

.0018

.0028

.0017

.0017

.00099

.0027

.36

.0066

.00034

.0041

.021

2.00

2.87

2.00

1.37

2.43

1.81

1.63

1.80

1.74

1.96

1 99

1.86

2.16

1.95

2.86

1.43

2.33

1.95

2.08

1.68

1.44

1 98

1.55

1.40

2 on

1.97

1.61

1.51

0

16

0

0

24

1

0

0

0

0

0

8

0

0

1 ..

2

24 ..

1

0

5

0

1

0

0

0

0

2 ..

0

1.7

.0018

.0094

.12

.0076

.00019

.0016

.0011

.65

.00037

.089

.0030

.041

.0061

.0013

.00044

.0035

.00026

.00050

.00090

.21

.0025

.0025

.0031

.025

2.61

2.03

1.83

1.81

1.76

2.60

2.08

2.04

2.62

2.21

2.83

2.03

3.05

1.87

1.51

3.30

2.28

4.12

1.67

1.84

1.65

2.43

2.30

2.31

1.60

0

21

0

7

24

23

0

0

0

11

0

13

0

0

27

6

27

12

4

24

10

13

0

4

1

1

27

0

>6.8

.0020

.029

.35

.0058

.0011

.0047

.0038

3.0

.0029

/ 2

.0032

.37

.022

.20

.0019

.0021

.0/4

.0017

.0011

.0029

.36

.0077

.0021

.00028

.0043

.016

>1.7

2.94

1.77

1.28

1.81

1.64

1.58

1.88

1.59

1.85

1.97

1.64

2.09

1.76

2.35

1.40

1.65

2.14

1.58

1.43

1.82

1.47

1.36

1.57

1.62

1.59

1.60

0

18

0

0

27

0

0

0

0

0

0

10

0

0

0

1

29

0

0

4

0

0

0

0

0

0

0

0

The diagrams in figures 3-6 provide graphical summaries of the correlation coefficients in tables 8-11. All 

the diagrams are similarly constructed. The diagram in 

figure 3, for example, summarizes the correlations 

between element contents in each of six vegetables and 

the soils of the gardens in which the vegetables grew. 

The garden soil is represented by the point at the center 

of the circular diagram. Each radius extending from 

this point represents a garden vegetable, as indicated. 

The distance of each point on the radius from the center 

of the circle is inversely proportional to the degree of 

positive correlation between the element content of the 

particular vegetable and the garden soil, among the 

sampling sites. Where the point lies near the center of 

the circle, the concentration of the element in the indicated vegetable shows a high degree of positive correlation with the concentration of the element in the soil.

Where the point lies near the inner circle, the concentration of the element in the vegetable is estimated to 

be nearly independent of the amount of the element in 

the soil. Where the point lies near the outer circumference of the circle, the concentration of the element in 

the vegetable displays a negative correlation with the 

concentration of the element in the soil; that is, vegetables containing higher concentrations of the element 

tend to occur in gardens where the concentration of the 

element in the soil is relatively low.

Figures 4, 5, and 6 contain similar diagrams summarizing the correlations of elements in the stems and 

leaves of trees with the amounts of the elements in the 

C, B, and A soil horizons, respectively. They also summarize the correlations of element concentrations among 

the three soil horizons.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C19

TABLE 8. Correlations between the amounts of elements in vegetables and garden soils in the high- and low-death-rate areas of Georgia

[r, product-moment correlation coefficient between logarithms of concentrations; N, number of pairs ommitted because concentration of element in one or both kinds of 

samples (vegetable or soil) was beyond the range of measurement by the analytical methods that were used;..-., insufficient data]

Element

Blackeyed peas Cabbage Com Green beans Lima beans Tomatoes

High- Low- High- Low- High- Low- High- Low- High- Low- High- Lowdeath-rate death-rate death-rate death-rate death-rate death-rate death-rate death-rate death-rate death-rate death-rate death-rate 

area, 29 area, 4 area, 28 area, 30 area, 29 area, 30 area, 30 area, 30 area, 30 area, 15 area, 30 area, 30 

pairs pairs pairs pairs pairs pairs pairs pairs pairs pairs pairs pairs

Al...__..__.

B_. ........

Ba-_. ......

Ca.. .......

Co.........

Cr.. .......

Cu.........

Fe... ......

K.. ........

Mg... ......

Mn.........

Ni.. .......

P..........

Sr.... ......

Ti..........

V..... ..

r N

..... 0.38 0

..... .05 14 .

..... .14 0

..... .06 0

............... 28 .

..... -.08 17 .

..... -.05 0

...... -.09 0

..... -.39 0

..... .23 0

..... -.09 0

..... .11 18

...... .20 0

...... -.72 24

..... -.13 0

............... 28 .

r

-0.68

-.83

-.75

.00

-.04

.76

.77

-.04

.65

-.05

.89 -.53

N

1

7,

0

0

4

3

0

0

0

0

0

0

1

0

4

r

0.45

.36

.53

.06

.10 -.11

.17 -.06

.40

.17

.11

-.77

-.17

N

0

13

0

0

28

a

0

0

0

0

0

27

0

23

0

25

r

0.19

.18

-.19

.25

.11

.50

.22

-.07

.03

.20

.50

-.06

-.08

-.09

-.37

N

4

15

0

0

29

4

0

0

0

0

0

25

0

1

0

25

r

0.13

-.01

.20

.12

.30

-.10

-.08

-.41

.28

-.08

-.92

.07 -.41

.26

N

0

16

0

0

29

?0

0

0

0

0

0

26

0

?A

3

29

r

-0.16

.17

-.44

.00

.25

.08

.19

.16

.42

-.10

.45 -.16

-.34

.01

N

4

18

0

0

30

20

0

0

0

0

0

14

0

1

1

30

T

0.26

-.37

.14

.00

-.10

-.39

-.09

-.28

-.11

-.27

.44

.11

.25

.07

N

0

15

0

0

29

11

0

0

0

0

0

20

0

25

0

?9

r

0.11

.12

.13

-.03

.50

.14

.49

.05

-.02

.21

.09

.07 -.02

.02

.01

N

4

13

0

0

15

10

0

0

0

0

0

2

0

1

0

?9

T

0.13

-.24

.13 -.11

.00

-.34

-.31

-.03

-.03

-.08

.08 -.10

.22 -.01

-.49

N

0

15

0

0

28

26

0

0

0

0

0

19

0

25

4

30

r

0.29

-.46

-.19

-.29

-.94

.16

-.65

.06

.29

-.22

.44

.15

-.53

.18

.06

N

1

9

0

0

10

9

0

0

0

0

0

0

0

1

1

14

T

-0.18

.05

-.30

.01

-.26

.09

-.26

.01

-.02

-.29

.13

-.33

-.41

-.50

N

0

6

10

0

30

11

0

0

0

0

0

28

0

26

1

27

T

-0.10

-.36

-.58

.34

.42

.65 -.12

.24

-.01

.01

.07

.01

-.10

N

4

IS

0

0

29

25

0

0

0

0

0

30

0

1

6

30

VEGETABLES AND GARDEN SOILS

Comparison of the compositions of garden soils in 

the high- and low-death-rate areas indicates that those 

in the high death-rate area tend to contain significantly 

lower concentrations of nearly all elements studied 

(table 5). This difference, which reflects the difference 

in the character of the bedrock geology in the two areas 

and the greater maturity of the soil in the high-deathrate area, is not apparent in the compositions of most 

of the vegetables, with the possible exceptions of cabbage and green beans. Cabbages from the high-deathrate area, like the garden soils, tend to contain lower 

concentrations of aluminum, chromium, iron, nickel, 

and titanum; other elements, except for boron and 

molybdenum, appear to be about equally concentrated 

in cabbages from the two areas in spite of their generally higher concentrations in soils of the low-death-rate 

area. The concentrations of several elements in green 

beans similarly appear to reflect the compositional differences in the soils between the two areas, but those in 

the other vegetables, in general, do not.

The correlations between the element contents of 

vegetables and of garden soils within each of the two 

areas, as indicated by the correlation coefficients (fig. 3 

and table 8), also fail to indicate any general relationship between vegetable and soil compositions. About 

half of the correlation coefficients are positive and half 

are negative, and there seems to be little or no consistency of correlation within elements, vegetables, or 

areas. The indication is that the greater number of the 

coefficients are spurious, resulting largely from chance, 

and are not reproducible.

It is reasonable to conclude, therefore, that the compositions of garden vegetables within both the highand the low-death-rate areas are generally independent 

of the compositions of the soils in which they are grown. 

Some correspondence between the composition of cabbages and green beans and the compositions of the soils 

does appear to be present, on a broader scale, between 

the high- and low-death-rate areas; these two vegetables tend to exhibit some of the same compositional 

differences as do the soils from the two areas.
C20

HIGH-DEATH-RATE AREA 

Blackeyed peas

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY 

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA

Green beans ALUMINUM

BARIUM

BORON

CALCIUM

CHROMIUM

COBALT

COPPER

IRON

FIGURE 3. Correlations between the amountsi of elements in garden soils and the amounts in vegetables from the high and 

low cardiovascular death-rate areas of Georgia. Distance of the point on the radius from the center of the circle is inversely 

proportional to the correlation of the amount of the element in the vegetable and the amount in the garden soil.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C21

HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA 

-IHIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA 

Blackeyed peas

MAGNESIUM POTASSIUM Green beans

MANGANESE STRONTIUM

NICKEL

TITANIUM

PHOSPHORUS VANADIUM

FIGURE 3. Continued
C22

HIGH-DEATH-RATE AREA

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY 

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA 

-IALUMINUM COBALT

BARIUM COPPER

BORON GALLIUM

CALCIUM IRON

CHROMIUM LANTHANUM

FIGURE 4. Correlations between the amounts of elements in the C horizon of uncultivated soils (center of circles) and the 

amounts in the A and B soil horizons and in the stems and leaves of trees. Triangles represent soil correlations; dots 

represent stems, squares represent leaves, of trees. Distance of the symbols on- the radii from the center of the circles is 

inversely proportional to the correlation of the amounts in the samples.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C23

HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA

A horizon

LEAD

MAGNESIUM

MANGANESE

NICKEL

NIOBIUM

PHOSPHORUS

POTASSIUM

SCANDIUM

SODIUM

Maple

STRONTIUM

FIGTJBE 4. Continued
C24

HIGH-DEATH-RATE AREA 

A horizon

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY 

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA

Maple TITANIUM

VANADIUM

LOW-DEATH-RATE AREA

-1-

YTTRIUM

ZINC

YTTERBIUM ZIRCONIUM

FIGURE 4. Continued
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C25

TREES AND UNCULTIVATED SOILS

Comparisons of the element content of the three horizons of uncultivated soils (table 7) and of eight species 

of trees (table 6) from the two death-rate areas indicate 

that concentrations of most elements in both soils and 

trees tend to be higher in the low-death-rate area. 

Similar trends were shown earlier in this report for 

garden soils but the trends were not apparent, for the 

most part, in the garden vegetables. The ability to discriminate between the two areas on the basis of tree 

analyses as a whole contrasts with discriminations based 

on vegetable analyses, and the better discrimination 

using trees may be caused by their growth habit which 

also contrasts with that of vegetables. All vegetables 

that were sampled are annuals that grow only one season 

and are then harvested before they are mature. Thus 

they have only a short period of time available for absorbing elements from the soil, whereas trees may absorb 

elements for periods of many years. Vegetables have 

shallow root systems, in contrast to trees which have 

deep and widespread roots. Trees, therefore, may be 

more effective than vegetables in reflecting the chemical 

nature of the soil on which they grow.

Of the eight species of trees, oak appears to be the 

most sensitive to the variation in element content of soils 

from the two death-rate areas. This relationship of oak 

to uncultivated soils resembles that of cabbage to garden 

soils. Sweetgum trees follow oak in sensitivity to soil

composition, and sassafras and smooth sumac seem to be 

the least sensitive species (table 6).

Stems and leaves appear to vary independently in 

containing amounts of elements that are significantly 

different in the two areas. Only some elements (for example, nickel and lead) in some trees (for example, 

blackgum and oak) show significant differences in contents in stems and leaves simultaneously.

Caution should be used in making generalizations of 

tree-soil relationships based on data presented in this 

report. The concentrations of the elements that were 

studied in Georgia soils are all believed to be within the 

"normal" range. The fact is well known that some trees, 

if growing on soils that contain highly anomalous 

amounts of certain elements (for example, soils overlying mineral deposits), contain anomalous amounts of 

the elements in which the soil is enriched.

Correlations of the amounts of elements in tree stems 

and in leaves and the three horizons of uncultivated soils 

are given in tables 9-11 and are illustrated in figures 4-6. 

These correlations fail to indicate any general relationships between tree and soil compositions. As with the 

correlations of vegetables and garden soils, about half of 

the correlation coefficients given in these tables are positive and half are negative, and little or no consistency is 

apparent within elements, trees, or death-rate areas. 

These results indicate that the greater number of coefficients result largely from chance and are not 

reproducible.
C26 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 9. Correlations between the amounts of elements in trees and in the 

[r, product-moment correlation coefficient between logarithms of concentrations; N, number of pairs omitted because concentration of element in

Blackgum

Element

High-deathrate area, 30 

, and plant part analyzed pairs each of 

stems and

Low-deathrate area, 30 

pairs each of 

stems and

leaves leaves

Al, stems..- ..

leaves.. __ . B, stems.. ....

leaves.......

Ba, stems.....

leaves.. .....

Ca, stems.....

leaves. _ ...

Co, stems.....

leaves.......

Cr, stems.....

leaves.--.--.

Cu, stems.....

leaves.......

Fe, stems-....

leaves.......

K, stems. .....

leaves...--..

Mg, stems..-..

leaves _ ....

Mn, stems.. ..

leaves. .__--.

Ni, stems... _.

leaves.---...

P, stems. .....

leaves.---...

Pb, stems.....

leaves.......

Sr, stems. _ ..

leaves. ..... .

Ti, stems. ... ..

leaves. ._.___

V, stems.. ....

leaves.... _..

Zn, stems-....

leaves. ---...

r

_. -_.-__._............-. -0.31

......-............__._........ -.28

._..___........................ .36

............................... .25

............................... .20

.............................. .16

............................... -.36

............................... -.12

.............................. .02

............................... .65

............................... .16

.............................. .28

............................... -.17

............................... .18

............................... -.11

.............................. .22

............................... -.36

........--.-.......... ..... .16

............................... .02

............................... .25

.............................. -.15

............................... -.06

--..-.- ----.........-... -.19

---.-.-- --- .....-..-.. .34

...._...........___........... .15

.............................. .04

.............................. -.22

.............................. .00

............................... .21

.............................. .02

.............................. -.24

.............................. -.09

..... - ..-..-.--...-.... .44

.............._.._............ -.62

N

0

0

21

21

0

0

7

7

23

24

0

1

0

0

0

0

0

0

1

24

0

0

13

13

4

4

24

24

13

13

0

0

24

28

27

27

r

-0.17

-.19

.41

.10 -.13

-.33

.24

.08

.22

.30 -.01

.08

.31

-.08

-.23

-.38

-.15

-.34

.15

.43

-.06

.03

.38

.45

-.00

.26

.11

.19

.04

.23

-.17

-.15

.29

.08

-.20

-.30

N

9

9

18

18

0

0

0

0

3

3

0

0

0

0

0

0

0

0

3

18

0

0

1

1

0

0

4

4

0

0

0

0

24

23

0

0

Oak

High-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0.24 0

-.19 0

-. 13 21

-.25 21

.10 0.

.19 0.

.05 7

.02 7

.......... 30

.......... 30

.05 1

.14 0

-.11 0

-.34 0

.02 0

.13 0

.13 0

.38 0

-.30 0

-.04 6

-.25 0

-.35 0

-.43 12

.04 13

.12 0

.38 0

.13 24

-.17 24

.58 13

.47 13

-.03 0

.06 0

.......... 26

-. 26 27

.......... 27

.......... 27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0. 11 9

-.22 9

-. 35 18

.16 18

-.54 0

-.33 0

-.23 0

-.31 0

-. 11 14

.21 17

.11 1

-.26 0

.11 0

-.06 0

-.02 0

-.22 0

-.10 0

-.50 0

.20 0

.16 3

.03 0

.07 0

.30 0

.23 0

.11 0

.13 0

-.13 4

.12 4

-.03 0

.10 0

-.17 0

-.16 0

.91 27

.16 22

-.11 0

-.34 0

TABLE 10. Correlations

Persimmon

High-deathrate area, 30 

pairs each of 

stems and

leaves

r

-0.23

-.11

-.09

.18

.26

.25

.03

-.10

.01

.27

.19

-.13

-.09

.05

-.09

-.10

.35

-.02

.10

-.07

.14

.25

.17

.16

.06

-.07

.26

.15

-.34

-.23

-.01

-.93

between

N

1

0

22

21

1

0

7

7

29

28

3

3

1

0

1

0

0

0

2

12

1

0

13

12

4

4

24

25

14

13

1

0

28

29

27

27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0.26 9

-.24 9

-. 02 18

.24 18

-.33 0

-.34 0

-.14 0

-.15 0

-.07 23 .

.......... 30

-.16 3

-.15 1

.09 0

.18 0

-.27 0

-.09 0

.19 0

-.07 0

.01 0

-.11 2

-.05 0

-.01 0

-.08 0

-.26 0

.24 0

.19 0

.15 5

.28 5

.03 0

.07 0

-.16 0

-.17 0

......... 25

-. 12 26 .

-.31 0

.18 10

Red maple

High-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0. 13 0

-.18 0

-. 30 21

.15 21

.23 0

.34 0

-.08 7

-.12 7

.......... 29

.......... 29

.10 3

-.13 2

-.37 0

-. 13 0

.10 0

.15 0

-.24 0

-.05 0

-.09 0

-.28 2

-.14 0

-.13 0

.62 15

.57 20

.02 4

.21 4

-.57 25

-. 18 25

.59 13

.59 13

.17 0

-.13 0

-.00 26 .

.......... 28 .

.50 27

.26 27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

0.01 9

-.22 9

.24 18

.09 18

.01 0

-.09 0

.01 0

-.08 0

.......... 30

.......... 30

-.09 1

.02 0

-.06 0

-.05 0

-.34 0

-.19 0

.16 0

-.01 0

.09 0

.20 0

-.48 0

-.51 0

.21 3

.52 0

.11 0

-.12 0

.24 4

.18 4

.08 0

.08 0

-.36 0

-.16 0

.......... 29

.......... 28

.06 0

-.12 0

the amounts of elements in trees and in the

[r, product-moment correlation coefficient between logarithms of concentrations; N, number of pairs omitted because concentration of element in

Blackgum

Element,

Al, stems. ._

leaves _ . ...

B, stems. .....

leaves.......

Ba, stems......

leaves.---....

Ca, stems......

leaves.......

Co, stems......

leaves.... ....

Cr, stems...--.

leaves.-.--...

Cu, stems _ ...

leaves........

Fe, stems.---..

leaves........

K, stems......

leaves. ______

Mg, stems.....

leaves. ......

Mn, stems.. .

leaves......

Ni, stems.-..

leaves......

P, stems... ...

leaves. ......

Pb, stems.....

leaves. ......

Sr , stems .

leaves.... .

Ti, stems _ .

leaves. ______

V , stems......

leaves. . . .

Zn, stems

leaves. ..._._

High-deathrate area, 30 

and plant part analyzed pairs each of 

stems and

leaves

r

.............................. -0.12

.............................. -.17

.............................. -.11

.............................. -.41

....._........................ .32

.............................. .35

.............................. -.13

.............................. -.16

.............................. .93

.............................. .68

.............................. .21

.............................. .18

.............................. -.08

.............................. .01

.............................. -.04

............................. .12

. ....-.._...-...._._._..__. -.38

.............................. .18

.............................. .08

.............................. .16

.............................. -.15

.............................. -.08

.............................. .61

.-..-......................._. .64

----..-.--......_.._..___.__ .27

.............................. .40

----...._........_...........- -.99

--.... ...-_..__.____..___ -.87

--..-. .-.._._.__.__.__ .01

-- ---- ..-..___._...._._ .31

.............................. -.28

- --.- ..--._..____...__ -.09

.............................. -.43

---------.--....-__...____.._ -.01

N

0

0

20

20

0

0

9

9

26

26

0

1

0

0

0

0

0

0

7

24

0

0

21

21

3

3

27

27

21

21

0

0

24 .

28

27

27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r

-0.33

-.17

.09

-.17

.01

-.40

.08

-.02

.09

.18

.19

.16

.49

-.03

-.02

-.02

-.11

-.32

.17

.84 -.30

-.03

.24

.34

.06

.22

-.09

.41

-.07

.12 -.22

-.09

.08

-.29

-.02

N

7

7

16

16

0

0

0

0

4

4

0

0

0

0

0

0

0

0

3

18

0

0

?

?,

0

0

5

5

1

1

n

n

?4

23

?:

2

Oak

High-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0.41 0

-.10 0

-. 01 20

-.18 20

.20 0

.31 0

.16 9

-.08 9

.......... 30

.......... 30

.01 1

.12 0

.05 0

-.25 0

.08 0

-.06 0

.06 0

.32 0

-.33 0

-.19 6

-.25 0

-.32 0

.39 20

.50 20

.28 3

.40 3

-.50 27

-.73 27

-.21 21

.03 21

.08 0

.16 0

-.00 26 .

-.78 27

.......... 27

.......... 27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0. 18 7

-.19 7

-. 19 16

-.11 16

 .59 0

-.52 0

.08 0

.02 0

-.16 14 .

.32 17 .

.13 1

-.02 0

.12 0

-.11 0

.11 0

-.05 0

-.14 0

-.53 0

.13 0

.18 3

-.16 0

-.27 0

.12 1

.17 1

-.06 0

-.11 0

-.02 5

.10 5

-.02 1

-.01 1

-.22 0

-.04 0

......... 27 .

.69 22

-.48 2

-.19 2

Persimmon

High-deathrate area, 30 

pairs each of 

stems and

leaves

r

-0.07

-.04

.10

-.14

.19

.20

-.16

-.30

.19

.08

.09

-.24

.02

.06

-.03

.00

.22

-.30

.02

-.15

.36

.18

.37

-.22

-.99

-.98

-.27

-.16

-.14

-.15

N

1

0

20

20

1

0

9

9

30

30

3

3

1

0

1

0

0

0

3

12

1

0

21

20

3

3

27

27

21

21

1

0

28

29

27

27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0. 19 7

-.09 7

.31 16

.24 16

-.58 0

-.56 0

-.19 0

- 38 0

.36 23 .

......... 30 .

.01 3

.03 1

-.02 0

.14 0

-.03 0

-.01 0

.16 0

-.14 0

-.04 0

.06 2

-.11 0

-.03 0

-.07 1

-.25 1

.17 0

.14 0

.26 6

.22 6

.05 1

.11 1

-.01 0

-.05 0

-.80 25

-.07 26

-.29 2 .

.23 2

Red maple

High-deathrate area, 30 

pairs each of 

stems and

leaves

r N

-0. 18 0

.01 0

-. 61 20

.04 20

.30 0

.33 0

-.44 7

-.29 9

......... 30 .

......... 30 .

.29 3

.04 2

-.07 0

-.03 0

-.04 0

.13 0

-.20 0

-.12 0

-.29 0

-.22 2

-.10 0

-.19 0

.51 20

.47 22

.24 3

.38 3

-.82 27

-.87 27

-.01 21

 . 11 21

.14 0

-.06 0

-.00 26 .

-.01 28 .

......... 27

......... 27

Low-deathrate area, 30 

pairs each of 

stems and

leaves

r N

0.06 7

-.27 7

.06 16

.44 16

-.12 0

-.33 0

.03 0

.18 0

......... 30

......... 30

.09 1

.14 0

-.12 0

-.20 0

-.13 0

.10 0

.14 0

-.03 0

.11 0

.28 0

-.60 0

-.62 0

.30 4

.52 11

-.05 0

.02 0

.20 5

.21 5

.09 1

.22 1

-.35 0

.04 0

......... 29

.......... 28

.18 2

-.09 2
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C27

C horizon of uncultivated soils in the high- and low-death-rate areas of Georgia

one or both kinds of samples (tree or soil) was beyond the range of measurement by the analytical methods that were used;. ., insufficient data]

Sassafras Smooth sumac Sweetgum Black cherrv

Element, and plant part analyzed

High-deathrate area, 17 

pairs each of 

stems and 

leaves

Low-deathrate area, 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

stems and 

leaves

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

High-deathrate area, 28 

pairs each of 

stems and 

leaves

Low-deathrate area, 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

stems and 

leaves

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

N N N N N N N N

Al, stems _ .. .............

leaves. ....-. - ----......

B, stems.. -.._._ .

leaves. ...... .... ....... _.

Ba, stems.... _ ...... ......

leaves ......................

Ca, stems.. -. __ .

leaves-.-. . .

Co, stems 

leaves .. --------------.

Cr, stems. ....... .... .-....

leaves.. .. ... --- ..

Cu, stems.. ..

leaves . .

Fe, stems.. _ - 

leaves. .. ..... ... . ....

K, stems.. --------------

leaves.-... .....-......__ .

Mg, stems ..

leaves ....... .... .... . ..

Mn, stems.

leaves--..- _...-.__-. ._

Ni, stems 

leaves. ...... _. --.. - .

P, stems.. _ . _ 

leaves. _...... _--,-.

Pb, stems 

leaves. ..... ... ... ........

Sr, stems..---.-. ---------

leaves 

Ti, stems.. ._..___-_.__... ...

leaves. .-.- - .... ......

V, stems - .

leaves - -...-. -. - ..

Zn, stems ._. 

leaves.--.--..--..-.- _ ....

._ 0.12

.- . .01

. .. . .12

...__-_-. . -.27

.. . .10

. . . -.02

. .-_- -.03

.. .. .19

.... ..- -.25

 -.._ -.02

- .. -.05

.. .. .02

.. .... .23

.. . .16

...-__-_ .. -.11

.- - -- .21

. . -.... -.10

. ..- -.02

..-.... .26

.. -. ... .31

.-... .. -.05

.... .. .60

...... - .04

. .. -.13

. ..... -.50

....-.. -.42

..-. -.39

...... . . -.42

.-._. .. -.41

..--..-.. . -.16

.-. .. - .41

0

0

11

11

0

0

4

4

17 .

17 .

1

0

0

0

0

0

0

0

0

3

0

0

7

7

1

1

14

14

8

8

0

0

8

13

16

16

-0.32 -.16

-.10

-.30

-.32

-.35

-.16

-.37

-.24

-.08

-.11

-.00

-.31

.06

.06 -.08

.00 -.12

.04 -.01

.12

.40 -.07

.23

.23

.20 -.26

-.32

-.32

-.36

-.09

.47 -.12

.07

8

8

6

6

0

0

0

0

26 ..

27 ..

0

0

0

0

0

0

0

0

0

2

0

0

0

0

0

0

6

4

0

0

0

0

18

20 ..

0

0

0.00

.07

.31

.22

.36

.28 -.05

.24

-.09

.27 -.21

-.32

.07

.22

.18

.11 -.23

-.08

-.23

-.52

-.23

-.21

.75

.15 -.86

-.14

.34

.42 -.13

-.07

.50

-.32

-.78

0

0

21

21

0

0

7

7

30

30 .

0

0

0

0

0

0

0

0

0

3

0

0

15

20

4

4

25

24

13

13

0

0

27 .

27

27

27

-0.04 -.27

-.32

-.13

-.25

-.27

-.25

-.04

.20

.20 -.15

-.08

-.05

.09 -.11

-.11

-.01

-.04

-.25

-.01

.16

.29

.09 -.10

-.18

.23

.28

.44 -.02

-.05

-.35

.25 -.34

-.43

9

9

18

18

0

0

0

0

25 .

30 -

3

1

0

0

0

0

0

0

0

0

0

0

7

9

0

0

5

4

0

0

0

0

28

23 .

0

0

-0.04

.16

.29

.23

.16

.24 -.07

-.23

-.00

.29 -.06

-.01

.05

.19 -.26

-.07

-.21

.04

.05

.09 -.12

-.19

.53

.38 -.27

-.64

.69

.68

.09 -.17

.00

.90

0

0

20

20

0

0

7

7

26

W

0

0

0

0

0

0

0

0

0

6

0

0

13

12

4

4

22

22

12

12

0

0

25 .

27 _

25

25

-0.08 -.25

-.29

-.23

-.26

-.21

.22

.30

.92

.07

.09 -.35

-.15

-.02

-.15

-.01

.20

.08

.30 -.26

-.26

.33

.31 -.14

.24

.06 -.20

.14 -.09

-.20

-.43

-.19

-.02

9

9

16

16

0

0

0

0

24

27 .

0

0

0

0

0

0

0

0

0

3

0

0

0

0

0

0

5

4

0

0

0

0

27

W

0

0

-0.23 -.03

.09

.12

.24

.32 -.19

-.10

-.00

.14

.13 -.24

-.06

.19

.27

.38

.23

.24

.23 -.10

-.17

.26 -.19

.20

.17

.26 -.19

.46

.67 -.10

-.03

-.45

-.82

-.00

0

0

21

21

0

0

7

7

28

30 .

1

2

0

0

0

0

0

0

4

9

0

0

17

12

4

4

24

25

13

13

0

0

26

28 .

27

27

-a is -.21

.02

.27 -.32

-.24

.02 -.23

-.17

-.23

-.14

.11

.25 -.34

-.18

-.12

-.20

-.08

-.16

-.05

-.08

.43

.53

.21

.20

.14

.34 -.07

-.01

-.15

-.27

-.58

.23

.50

9

9

18

18

10

0

0

0

21

30

2

0

0

0

0

0

0

0

0

6

0

0

9

2

0

0

5

5

0

0

0

0

20

36

0

0

B horizon of uncultivated soils in the high- and low-death-rate areas of Georgia

one or both kinds of samples (tree or soil) was beyond the range of measurement by the analytical methods that were used;...., insufficient data]

Sassafras Smooth sumac Sweetgum Black cherry

Element, and plant part analyzed

High-deathrate area, 17 

pairs each of 

stems and 

leaves

Low-deathrate area, 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

stems and 

leaves

Low -deathrate area, 30 

pairs each of 

stems and 

leaves

High-deathrate area, 28 

pairs each of 

stems and 

leaves

Low-deathrate area, 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

stems and 

leaves

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

N N N N N N N N

Al, stems...............----.

leaves.-. __ ...... ........

B, stems.-.... ....-........

leaves. -. ________._._____.

Ba, stems---..-----.-----....

leaves......................

Ca, stems..---. ----.-.-....

leaves... .............. _ ..

Co, stems....... ..--.. .

leaves. ....--..----.-.......

Cr, stems..... . ..-... ....

leaves ..-....-----..----..

Cu, stems.-- -----------

leaves-....-. _ _._. ___.

Fe, stems 

leaves..-.-..--.---.- ... ..

K, stems... ...... ............

leaves..- ..... . .

Mg, stems.... ___________

leaves. .......... ......

Mn, stems.... ______________

leaves. __ __ ._._.._____

Ni, stems...

leaves........... .....

P, stems....... ...... .. .

leaves...

Pb, stems.

leaves .. . ... . .

Sr, stems. .. . . ....

leaves... __ _________ _

Ti, stems,

leaves. .

V, stems.. ..

leaves............

Zn , stems

leaves. .

...... ...- . -0.23

. . ... -.18

..__--- .33

... . ...... -.63

-------- .26

-------- .09

..__ .._ . -.24

.-.... -.01

.__ .__ ___ -.32

....... .. .... -.09

._ __ -.47

..... .. - .05

.-..----_-- -.06

 ._._-. . -.02

 ... ._. -.01

.......___ _. .38

 --.-- -.32

--...-........ .01

--...... .... .28

.... .... .47

-. .-...._... .45

-._____ - -.03

 .-.. ..._ .30

- .-- .22

........ .... -.35

-...___________. -.37

--.----.--...... .09

..... ........ -.02

._-.-. __-._ -.30

- -------. -.90

0

0

10

10

0

0

7

7

17 ..

17 .

1

0

0

0

0

0

0

0

0

3

0

0

9

9

1

1

17

17

12

12

0

0

9

13

15

15

-0.36 -.08

.34 -.01

-.27

-.29

-.17

-.19

-.21

-.12

-.29

-.15

-.12

-.08

.00 -.13

-.01

.07 -.09

-.17

.05

.44

.16

.16

.28

.16 -.15

-.26

-.19

-.29

-.35

-.54

-.14

-.11

6

6

14

14

0

0

0

0

26 ..

27 ..

0

0

0

0

0

0

0

0

0

2

0

0

1

1

0

0

7

5

1

1

0

0

18

20

2 -

2

0.06 -.01

-.06

-.19

.43

.32

.05

.26

-.01

.37 -.08

.45

.10

.06

.06 -.04

-.16

-.09

-.26

-.40

.25 -.64

.74

.47 -.50

-.85

.31

.16 -.25

-.17

-.21

-.78

0

0

20

m

0

0

9

9

29

30 -

0

0

0

0

0

0

0

0

0

3

0

0

22

23

3

3

27

27

21

31

0

0

0 _

0

27

27

-0.09 -.21

.10 -.37

-.30

-.41

-.11

.03

.58

.15

.00 -.11

-.10

-.06

-.08

-.19

-.04

-.13

-.31

-.09

-.15

.25

.14 -.24

-.27

.20

.40

.24

.12

.14 -.36

-.03

-.52

-.36

7

7

16

16

0

0

0

0

25 ..

30 ..

3

1

0

0

0

0

0

0

0

0

0

0

8

10

0

0

6

5

1

1

0

0

28

23 ..

2

2

0.19

.14

-.61

-.07

.14

.19 -.33

-.25

.08

.15

.15

.18

.18

.33 -.26

-.08

-.17

-.14

.01

.06

.60

.48

.47

.41 -.94

-.91

-.22

-.07

-.09

-.15

-.00

0

0

19

19

0

0

9

9

26

28 .

0

0

0

0

0

0

0

0

0

6

0

0

19

19

3

3

25

25

19

19

0

0

25 -

27 .

25

25

-0.17 -.35

-.18

.12 -.36

-.48

-.08

-.08

.92

.15

.20 -.32

-.23

-.16

-.51

-.00

.23

.07

.30 -.30

-.27

.35

.28

.02

.13

.17 -.01

.19 -.08

-.11

-.29

-.01

.07

7

7

13

13

0

0

0

0

24 .

27 .

0

0

0

0

0

0

0

0

0

3

0

0

1

1

0

0

6

5

1

0

0

0

27

25 .

2 -

2

-0.25 -.11

-.05

-.46

.24

.31 -.24

-.38

.12

. 14

-.19

-.16

.10 -.04

.43

.31

.14

.14 -.03

-.20

.35 -.21

.51

.51 -.50

-.01

.05 -.06

-.11

.35 -.57

0

0

20

20

0

0

. 9

9

29

30 -

1

2

0

0

0

0

0

0

4

9

0

0

22

20

3

3

27

28

21

21

0

0

26

28 .

27

27

-0.45 -.26

.40

.36 -.46

-.47

-.03

-.00

-.23

-.18

.01 -.19

-.10

-.24

-.02

-.12

-.20

.16

.37

.07

.07

.42

.48

.24

.16

.26

.47

.07

.11 -.02

-.00

.04

.03

.56

7

7

16

16

0

0

0

0

22

30

2

2

0

0

0

0

0

0

0

6

0

0

10

2

0

0

6

6

1

1

0

0

26

30

2

2
C28

HIGH-DEATH-RATE AREA 

A horizon

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA

-1-^ ^- HALUMINUM

BARIUM

BORON

CALCIUM

CHROMIUM

LOW-DEATH-RATE AREA

-1-

COBALT

COPPER

GALLIUM

IRON

LANTHANUM

FIGURE 0. Correlations between the amounts of elements in the B horizon of uncultivated soils (center of circles) and the 

amounts in the A horizon of soils and in the stems and leaves of trees. Triangles represent soil correlations; dots represent 

stems, squares represent leaves, of trees. Distance of the symbols on the radii from the center of the circles is inversely 

proportional to the correlation of the amounts in the samples.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C29

HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA

A horizon

LEAD

MAGNESIUM

MANGANESE

NICKEL

PHOSPHORUS

POTASSIUM

SCANDIUM

SODIUM

NIOBIUM STRONTIUM

FIGURE 5. Continued
C30

HIGH-DEATH-RATE AREA

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY 

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA

TITANIUM

VANADIUM

mERBIUM

LOW-DEATH-RATE AREA

YTTRIUM

ZINC

ZIRCONIUM

FIGURE 5. Continued
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C31

CORRESPONDENCE AMONG THE COMPOSITIONS 

OF SOIL HORIZONS

Correlations of the amounts of elements in samples of 

the three horizons of uncultivated soil are given in table 

12 and illustrated in figures 4-6. The correlations of elements between the A and the C horizons (fig. 4 and 

table 12) are 'all positive except for boron, gallium, and 

strontium in the high-death-rate area and lanthanum in 

the low-death-rate area. The correlations of the amounts 

in the B and C horizons (fig. 4 and table 12) are all 

positive except for gallium and strontium in the highrate area. The correlations of the amounts in the A and

B horizons (fig. 5 and table 12) are all positive except 

for lanthanum in the low-death-rate area.

These data indicate that the amounts of most elements in the three soil horizons are strongly interdependent. The elements that have negative correlations 

are nonnutritive, except boron which is a micronutrient; 

their differences in amounts in soil samples from the 

two death-rate areas are not significant at the 95-percent 

level of confidence (table 7).

The results of this study also suggest that in searching for differences in amounts of most elements in the 

soils of the two death-rate areas, any one of the three 

soil horizons could be sampled alone.
C32 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

HIGH-DEATH-RATE AREA

Blackgum

LOW-DEATH-RATE AREA

-1-

HIGH-DEATH-RATE AREA LOW-DEATH-RATE AREA

Sassafras ALUMINUM COBALT

BARIUM COPPER

BORON IRON

CALCIUM LEAD

CHROMIUM MAGNESIUM

FIGURE 6. Correlations between the amounts of elements in the A horizon of uncultivated soils (center of circles) and the 

amounts in stems and leaves of trees. Dots represent stems, squares represent leaves. Distance of the symbols on the radii 

from the center of the circles is inversely proportional to the correlation of the amounts in the samples.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C33

HIGH-DEATH-RATE AREA

-lLOW-DEATH-RATE AREA 

-1-

MANGANESE

NICKEL

PHOSPHORUS

HIGH-DEATH-RATE AREA LDW-DEATH-RATE AREA 

Blackgum

STRONTIUM

TITANIUM

VANADIUM

POTASSIUM

Sassafras

ZINC

FIGURE 6. Continued
C34 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 11. Correlations between the amounts of elements in trees and in the A 

[r, product-moment correlation coefficient between logarithms of concentrations; N, number of pairs omitted because concentration of element in one

Blackgum

High-deathElement, and plant part analyzed rate area, 30 

pairs each of 

stems and 

leaves

leaves

Fe, stems...-.-... _ -..---.

Ni, stems.. ................ .

leaves---.... _ . _ --.-...

Sr, stems...-.-..----.---....

leaves....-.--.....-.-.-...

r

................ -0.42

................ -.32

................ -.10

................ -.38

................ .06

................ .11

................ -.21

................ -.11

.............. -.23

KA

................ -.03

--.-.... --.. .09

--.--....-.-. -.03

................ -.08

................ -.21

................ .03

................ -.37

..--...... ... .18

................ -.01

................ -.51

................ -.12

 .-._..- ... -.17

--.-- -.. .51

................ .60

................ .17

................ .23

................ -.57

--.......-.....- .39

............... -.21

................ -.05

................ -.27

................ -.17

 *U2

................ -.46

............... -.09

N

1 

1 

20 

20 

0 

0 

7 

7 

24 

25 

0 

1 

0 

0 

0 

0 

0 

0 

1 

24 

0 

0 

22 

22 

0 

0 

23 

23 

19 

19 

0 

0 

25 

28 

23 

23

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.21 

-.24 

.69 

.08 

.08 

-.14 

.16 

.11 

.17 

.26 

.18 

.24 

.25 

-.13 

-.10 

-.19 

-.07 

-.27 

.13 

.71 

-.18 

.03 

-.10 

-.12 

.17 

.31 

.46 

.55 

.05 

.29 

-.17 

-.20 

.01 

-.03 

-.24 

.06

N

4 

4 

17 

17 

0 

0 

1 

1 

5 .

5 .

0 

0 

0 

0 

0 

0 

0 

0 

3 

18 

0 

0 

2 

2 

0 

0 

3 

3 

1 

1 

0 

0 

24 

23 

1 

1

Oak

High-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.39 

-.17 

-.08 

.39 

.19 

.37 

.14 -.26

-.15 

.18 

-.16 

-.40 

-.10 

-.02 

.00 

.27 

-.50 

-.39 

-.07 

-.05 

-.24 

.12 

.06 

.21 

-.38 

.10 

-.52 

-.55 

.20 

.37 

-.00 

-.78 

.21 

.01

N

1 

1 

20 

20 

0 

0 

7 

7 

30 

29 

1 

0 

0 

0 

0 

0 

0 

0 

0 

6 

0 

0 

22 

22 

0 

0 

23 

23 

19 

19 

0 

0 

26 

27 

23 

23

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.29 

-.20 

.41 

.46 

-.38 

-.21 

-.01 

-.08 

-.46 

.05 

.14 

-.01 

.11 

-.14 

.06 

 .11 

-.17 

-.57 

.23 

.24 

-.17 

-.18 

.17 

.14 

.20 

.18 

.38 

.43 

.05 

.11 

-.26 

-.13 

-.91 

.55 

-.28 

-.25

N

4 

4 

17 

17 

0 

0 

1 

1 

16 .

1 

0 

0 

0 

0 

0 

0 

0 

0 

3 

0 

0

1 1

0 

0 

3 

3 

1 

1 

0 

0 

27 

22 .

1 

1

Persimmon

High-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.04 

.06 

.12 

-.25 

.17 

-.04 

-.26 

-.12

.24 

.13 

.03 

-.01 

-.00 

-.01 

-.03 

.01 

.08 

-.27 

.20 

-.20 

.18 

-.10 

.35 

-.09 

-.10 

-.21 

-.22 

-.08 

-.29 

-.14 

-.00

-.73 

-.26

N

2 

1 

21 

20 

1 

0 

7 

7 

25 

29 .

3 

3 

1 

0 

1 

0 

0 

0 

3 

12 

1 

0 

22 

22 

0 

0 

23 

24 

19 

19 

1 

0 

27 

29 

23 

23

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.25 

-.18 

.36 

.69 

-.21 

-.27 

.32 

.25 

.21

.09 

.05 

.09 

.18 

.03 

-.10 

.26 

-.09 

-.05 

.01 

-.07 

.07 

-.00 

-.21 

.19 

.07 

.30 

.28 

.18 

.16 

-.07 

-.17 

-.25 

-.07 

-.26 

-.07

N

4 

4 

17 

17 

0 

0 

1 

1 

2S

30

3 

1 

0 

0 

0 

0 

0 

0 

0 

2 

0 

0 

1 

1 

0 

0 

4 

4 

1 

1 

0 

0 

25 

26 .

1 

1

Red maple

High-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.21

-.15 

_ _ 44

-.'ll 

.20 

.24 

-.44 

-.46

.48 

.06 

-.04 

-.15 

-.08 

.28 

-.15 

-.12 

-.44 

-.41 

-.01 

-.16 

.23 

.06 

.21 

.11 

.31 

.01 

-.23 

-.43 

.24 

-.11 

-.00

.70 

.64

N

1 

1 

20 

20 

0 

0 

7 

7 

29 .

30 .

3 

2 

0 

0 

0 

0 

0 

0 

0 

2 

0 

0 

22 

22 

0 

0 

24 

24 

19 

19 

0 

0 

26 .

28 .

23 

23

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

r

-0.01 

-.18 

-.06 

.36 

.02 

-.04 

-.16 

.20

.19 

.19 

-.10 

-.18 

-.17 

-.08 

.10 

-.01 

.12 

.29 

-.69 

-.75 

.24 

.66 

-.02 

.04 

.33 

.56 

.16 

.21 

-.20 

.03

-.05 

-.17

N

4 

4 

17 

17 

0 

0 

1 

1 

30 

30 

1 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

4 

11 

0 

0 

3 

3 

1 

1 

0 

0 

29 

28 

1 

1

TABLE 12. Correlations between the amounts of elements in horizons of uncultivated soils in the high- and low-death-rate areas 

of Georgia

[r, product-moment correlation coefficient between logarithms of concentrations; N, 

number of pairs omitted because concentration of element in the sample from one 

or both soil horizons was beyond the range of measurement by the analytical 

methods that were used; ...., no data available]

High-death-rate area,

Element

Al..........

B...._.._ .

Ba._........

Ca..........

Co..........

Cr..........

Cu.........

Fe........

Ga.. .......

K.. ........

La..........

Mg.. ......

Mn........

Na.. ......

Nb........

Ni........

P......... .

Pb....... .

Sc ......

Sr.. ........

Ti......

V. .

Y.. .......

Yb........

Zn.........

Zr.. .......

AandB 

horizons

r

0.74 

-.21 

.68 

.68 

.50 

.56 

.59 

.75 

.23 

.95 

.68 

.82 

.68

.31

.26 

.62

.44 

.36 

.73

.75 

.79 

.77

.58

N

1

25 

0 

14 

27 

0 

0 

0 

21 

0 

19 

0 

0 

28

6 

24 

3 

28 

22 

21 

0 

6 

1 

0

?q

0

AandC 

horizons

r

0.39 

-.76 

.61 

.36 

.86 

.38 

.33 

.51 

-.38 

.81 

.46 

.46 

.51

.22 

.37 

.20 

.91 

.17 

-.31 

.76 

.30 

.34 

.27

.48

N

1 

24 

0 

12 

27 

0 

0 

0 

21 

0 

17 

0 

0 

28 

8 

25 

4 

27 

28 

21 

0 

6 

1 

1 

29

0

30 pairs

BandC 

horizons

T N

0.57 0 

.89 26 

.87 0 

.45 13 

.86 27 

.56 0 

.35 0 

.63 0 

-.41 21 

.88 0 

.73 20 

.66 0 

.82 0 

.87 27 

.68 7 

.19 22 

.62 6

2Q

.33 12 

-.13 23 

.81 0 

.31 6 

.40 1 

.29 1 

........ 29

.54 0

Low-death-rate area, 30 pairs

AandB 

horizons

r

0.82 

.55 

.70 

.39 

.84 

.86 

.81 

.82 

.77 

.96 

-.06 

.91 

.78 

.78 

.55 

.87 

.79 

.38 

.74 

.86 

.79 

.77 

.39 

.76 

.71 

.34

N

8 

18 

0 

1 

3 

0 

0 

0 

1 

0 

13 

0 

0 

1 

3 

1 

0 

5 

1 

2 

0 

0 

0 

0 

2 

0

AandC 

horizons

r

0.73 

.70 

.81 

.19 

.79 

.80 

.73 

.60 

.53 

.95 

-.15 

.67 

.62 

.74 

.78 

.83 

.82 

.30 

.79 

.83 

.75 

.50 

.60 

.49 

.52 

.34

N

10 

19 

0 

1 

2 

0 

0 

0 

1 

0 

13 

0 

0 

1 

3 

1 

0 

4 

1 

1 

0 

0 

0 

0

1

0

BandC 

horizons

r

0.73 

.60 

.70 

.51 

.86 

.79 

.78 

.53 

.71 

.97 

.03 

.64 

.78 

.85 

.79 

.85 

.70 

.71 

.78 

.89 

.67 

.45 

.36 

.43 

.47 

.54

N

11 

18 

0 

0 

1 

0 

0 

0 

0 

0 

13 

0 

0 

1 

3 

1 

0 

5 

0 

1 

0 

0 

0 

0 

2 

.0

CORRESPONDENCE BETWEEN THE COMPOSITIONS 

OF STEMS AND LEAVES OF TREES

The correlations that indicate the correspondence of 

stem and leaf analyses are given in table 13 and illustrated in figure 7. The correlations are all positive except for ash, lead, and zinc in cherry, lead in sassafras, 

and magnesium in sweetgum, all in samples from the 

high-death-rate area. The correlations are most highly 

positive for aluminum, barium, calcium, manganese, 

and strontium.

These data indicate that the amounts of most elements 

in stems and leaves are strongly interdependent, and 

that in searching for differences in element content of 

trees from the two death-rate areas, either stems alone 

or leaves alone, could be used.

SUMMARY

1. Of the 159 counties in Georgia, the nine counties 

of northern Georgia that were chosen for geochemical 

studies because of their low rate of death due to cardiovascular diseases also are among the 20 counties having 

the lowest rate for all causes of death, as well as being
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C35

horizon of uncultivated soils in the high- and low-death-rate areas of Georgia

or both kinds of samples (tree or soil) was beyond the range of measurement by the analytical methods that were used; ., insufficient data]

Smooth sumac Sweetgum Black cherry

Element, and plant part analyzed

High-deathrate area, 17 

pairs each of 

stems and 

leaves

Low-deathrate area, 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

stems and 

leaves

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

High-deathrate area, 28 

pairs each of 

stems and 

leaves

Low-deathrate area 27 

pairs each of 

stems and 

leaves

High-deathrate area, 30 

pairs each of 

steins and 

leaves

Low-deathrate area, 30 

pairs each of 

stems and 

leaves

N N N N N N

Al, stems... ---------- _ ...

leaves... _ ------ _ --....

B, stems.. ..................

leaves.. _ _ ............

Ba, stems...................

leaves. - ....... _ ........

Ca, stems __ ...... _ __ .

leaves..-........--,-......

Co, stems. _ ...............

leaves _ .. _ ............

Cr, stems... _ ..............

leaves _ _ ...............

Cu, stems................ ...

leaves. _ .____________....

Fe, stems...---.-.-.........

leaves. ___ ....... __ .

K, stems....................

leaves.....................

Mg, stems...................

leaves.

Mn, stems ....

leaves. . . .

Ni, stems. .......... ......

leaves.............. ......

P, stems....................

leaves.

Pb, stems..... __ ...... _ .

leaves..

Sr, stems.. .

leaves........ .....

Ti, stems __ ..... .

leaves.... .......... . . ..

V, stems....--------..-.-...

leaves.....................

Zn, stems. _ . _ . _ ... ....

leaves.

........ ..... -0.53

................ -.36

-- .-..... .48

......... .... -.41

................ .09

.............. .01

................ -.75

................ -.56

................ -.22

................ -.19

................ -.60

................ -.02

................ -.21

................ -.10

................ -.24

................ .26

................ -.68

................ -.25

- -..........- -.08

................ .18

................ .20

 ... .-.. -.15

................ .08

................ .28

...-...-.....--. -.99

................ .11

................ -.76

................ -.50

................ -.48

...... ....... -.29

................ -.11

--...-.-....... -.73

................ -.43

................ -.91

0

0

12

12

0

0

4

4

17

17 .

1

0

0

0

0

0

0

0

0

3

0

0

12

12

0

0

13

13

11

11

0

0

7

12

13

13

-0.47

-.15

.21

.12

-.23

-.25

.15

.12

-.15

.05

-.22

-.13

-.45

-.22

.06 -.12

-.15

-.06

-.23

-.23

-.04

.33

.13

.16

.30

.34

-.17

-.28

-.43

-.44

-.39

-.17

.05

.22

3

3

15

15

0

0

1

1

26 .

27

0

0

0

0

0

0

0

0

0

2

0

0

1

1

0

0

5

3

1

1

0

0

18

18

1

1

-0.18

-.02

-.32

-.46

.38

.38

.02

.21

.02

.33

.05

-.14

.02

.02

.04

-.04

-.27

-.44

-.26

-.20

.68

.74

.38

.16

-.44

-.09

.15

.09

-.00

.03

.11

-.50

.27

.26

1

1

20

20

0

0

7

7

29

30

0

0

0

0

0

0

0

0

0

3

0

0

23

25

0

0

23

23

19

19

0

0

27

27

23

23

-0.15

-.11

.20

.42

-.11

-.16

-.08

.04

.37

.28

.06

-.19

-.13

-.19

-.32

-.18

-.04

-.15

-.27

-.22

-.27

.11

.07

-.15

-.18

.39

.45

.14

.13

-.13

-.36

-.01

-.07

-.46

-.26

4

4

17

17

0

0

1

1

25

30

3

1

0

0

0

0

0

0

0

0

0

0

8

10

0

0

4

3

1

1

0

0

28

23

1

1

-0.07

.05

.07

.48

.33

.28

-.36

-.48

.31

.10

.04

.02

.13

.09

-.32

-.18

-.18

-.36

.14

.25 .

.36

.31

.25

.26

.18

-.45

-.46

-.43

.12

-.13

-.00

.37

.37

1

1

18

18

0

0

7

7

25 .

27 .

0

0

0

0

0

0

0

0

0

6

0

20

20

0

0

21

21

17

17

0

0

25

27 .

22

22

-0.21

-.48

-.19

-.28

-.28

-.24

-.12

-.26

.11

.21

-.40

-.28

-.26

-.62

.06

.23

.04

.17

-.24

-.17

.23

.13

.07

.23

.37

.30

.27

.13

-.35

-.55

.01

.25

4

4

14

14

0

0

1

1

25

27 .

0

0

0

0

0

0

0

0

0

3

0

0

1

1

0

0

4

3

1

1

0

0

27

25 .

1

1

-0.16

-.13

-.55

-.37

-.02

.07

-.18

-.25

-.01

-.09

-.02

-.23

-.10

-.15

-.11

.53

.35

-.05

-.25

.02

-.22

-.16

.09

.06

.20

-.05

-.42

-.19

-.26

-.11

-.03

-.57

-.01

-.03

1

1

20

20

0

0

7

7

27

30 .

1

2

0

0

0

0

0

0

4

9

0

0

23

22

0

0

23

24

19

19

0

0

26 W

23

23

-0.30

-.37

.22

.36

-.15

-.13

.10

.11

-.25

-.20

.07

-.10

.12

-.23

-.17

-.06

-.18

.21

.39

.14

.13

.53

.54

.17

.23

.24

.36

.14

.24

-.11

-.23

.16

.20

.55

4

4

17

17

0

0

1

1

21

30

2

2

0

0

0

0

0

0

0

6

0

0

10

2

0

0

4

4

1

1

0

0

26

30

1

1

among those with the very lowest rate for the cardiovascular diseases generally, and coronary heart disease 

specifically. The counties chosen for study in central 

and south-central Georgia are all among the 20 counties 

having the highest rate for all causes of death, and have 

mortality rates for the cardiovascular diseases roughly 

twice as high as those for the low-rate counties that 

were studied. In this one State, contrasts in mortality 

rates for cardiovascular diseases are found which are 

almost as great as can be found between any two counties in the United States. These contrasts are not due to 

random error, and almost certainly were not produced 

by the methods of data collection and classification.

2. The counties that have high cardiovascular death 

rates are located where Paleudult, Quartzipsamment, 

and Ochraquult soils predominate. These soils are derived from unconsolidated or slightly consolidated 

sands, sandy clays, and clays of the Atlantic Coastal 

Plain region. The counties with low death rates due 

to the same cause are located within the area of Hapludult soils that were derived from the weathering of 

rocks in the Appalachian Plateaus, Valley and Kidge, 

Blue Ridge, and Piedmont provinces.

3. The frequency of occurrence of the plants that were 

sampled differed in the two death-rate areas. The vegetables found most frequently in both areas were corn, 

green beans, tomatoes, and cabbage, and the most common trees were blackgum, persimmon, red maple, smooth 

sumac, and black cherry.

4. Estimates of experimental error in sampling soils 

indicated that in general the variation between the 

high- and low-death-rate areas is sufficiently large, in 

comparison with the variation between sites or between 

samples within sites, that compositional differences between soils from the two areas appear to be identifiable.

5. The concentrations of the elements that were 

studied in both garden soils and uncultivated soils tend 

to be significantly different in the two death-rate areas 

and are generally higher in the low-death-rate area.

6. Because of the similarities in element content of 

the soil horizons at a sample site, the differences in concentrations of almost all elements in uncultivated soils 

from the two areas could have been determined by 

sampling any one of the three soil horizons.

7. The cultivation of garden soils apparently has not 

greatly altered their content of the elements that were
C36

HIGH-DEATH-RATE AREA

STATISTICAL STUDIES IN FIELD GEOCHEMISTRY 

LOW-DEATH-RATE AREA HIGH-DEATH-RATE AREA

Sassafras ASH

ALUMINUM

BARIUM

BORON

CALCIUM

LOW-DEATH-RATE AREA 

-1-

CHROMIUM

COBALT

COPPER

IRON

LEAD

FIGURE 7. Correlations between the amounts of elements in stems and in leaves of trees. The center of the circles represents 

stems, and the dots represent leaves. Distances of the dots on the radii from the center of the circles is inversely proportional to the correlation of the amounts in samples of stems and leaves.
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA C37

HIGH-DEATH-RATE AREA 

-1-

LOW-DEATH-RATE AREA 

-1-

HIGH-DEATH-RATE AREA LOW- DEATH-RATE AREA

MAGNESIUM

MANGANESE

NICKEL

PHOSPHORUS

POTASSIUM

STRONTIUM

TITANIUM

VANADIUM

ZINC

Sassafras

FIGURE 7. Continued
C38 STATISTICAL STUDIES IN FIELD GEOCHEMISTRY

TABLE 13. Correlations between the amounts of elements in stems 

[r, product-moment correlation coefficient between logarithms of concentrations; N, number of pairs omitted because concentration of element

Blackgum

Element or ash High-deathrate area, 

30 pairs

Al-.-...----- -----

Ash.... ................. ..

B..... -----------------

Ba... ...---.--__.-_. ...

Co.. ......... . -------

Or. ................... .

Cu . - 

Fe.... - .. 

Mg. ... -------------

Mn. ................ ....

Ni...... ......... ........ .

P. .... .... .... .....

Pb . ...

Sr... .. -----------------

Ti___._ ........ ............

V........ .................

Zn--.-. . ._.

r

........ .......... 0.65

....... .-..... .49

. . .... .61

.-. .. ...- .91

--...--_-_-.. .67

........ .......... .93

-.-.-.-__--._. .53

.................. .32

____--_---._-- .54

 - .-- .44

. ... ........ .67

--... -..-.- .85

-.----..-...._- .77

- . ... . .62

.. . . . .30

......... ......... .65

....... ........... .58

. ..- .. .61

N

0 

0 

0 

0 

0 

3 

1 

0 

0 

0 

24 

0 

1 

0 

1 

0 

0 

28 

0

Low-deathrate area, 

30 pairs

r

0.65 

.73 

.54 

.26 

.76 

.94 

.72 

.54 

.92 

.50 

.02 

.72 

.87 

.31 

.62 

.83 

.83 

.57 

.27

N

0 

0 

0 

0 

0 

3

0 

0 

0 

0 

18 

0 

1 

0 

0 

0 

0 

26 . 

0

Oak Persimmon

High-death- Low-deathrate area, rate area, 

30 pairs 30 pairs

r

0.64 

.49 

.42 

.84 

.64

.54 

.54 

.44 

.32 

.36 

.81 

.64 

.55 

.35 

.41 

.50 

.... ... 

N

0 

0 

0 

0 

0 

29 

1 

0 

0 

0 

6 

0 

1 

0 

3 

0 

0 

28 ... 

0

r

0.61 

.70 

.35 

.71 

.77 

.46 

.68 

.56 

.69 

.49 

.19 

.51 

.51 

.67 

.73 

.69 

.54

.33

N

0 

0 

0 

0 

0 

18 

1 

0 

0 

0 

3 

0 

0 

0 

0 

0 

0 

28 

0

High-death- Low-deathrate area, rate area, 

30 pairs 30 pairs

r

0.85 

.41 

.41 

.79 

.40 

.95 

.45 

.28 

.62 

.72 

.43 

.73 

.39 

.18 

.56 

.93 

.77 

..........

N

1

0

1 

1

0 

27 ...

5 

1 

1 

0 

13 

1 

1 

0 

9 

1 

1 

30 ... 

0

r

0.80 

.12

.52 

.74 

.78

.48 

.31 

.64 

.60 

.46 

.80 

.75 

.54 

.54 

.89 

.58 "".'si"

N

0 

0 

0 

0 

0 

30

3 

0 

0 

0 

2 

0 

0 

0 

1 

0 

0 

28 

0

Red maple

High-deathrate area, 

30 pairs

r

0.72 

.53 

.40 

.88 

.86

.30

.50 

.56 

.63 

.39 

.89 

.82 

.49 

.66 

.87 

.57 

.--.- 

N

0 

0 

0 

0 

0 

30 ..

4 

0 

0 

0 

2

0 

13 

0 

5 

0 

0 

29 .. 

0

Low-deathrate area, 

30 pairs

r

0.66 

.41 

.33

.77 

.65

.64 

.73 

.73 

.50 

.33 

.91 

.82 

.45 

.36 

.87 

.40

~"".~42~

N

0 

0 

0 

0 

0 

30 

1 

0 

0 

0 

0 

0

11

0 

0 

0 

0 

29 

0

studied, if judged by the concentrations of these elements in uncultivated soils.

8. The difference in element composition of soils from 

the two areas is not apparent in analyses of most vegetables from the two areas. Only cabbage and green 

beans tend to reflect, on a broad scale, the difference in 

amounts of certain elements in soils from the two areas.

9. Correlations between the element content of garden soils and of vegetables fail to indicate a general relationship between the composition of vegetables and the 

soils on which they grew.

10. Within each area, the results fail to demonstrate 

any consistent correlations between the element content 

of trees and the composition of any soil horizons at the 

sites where the trees grew.

11. The concentrations of elements in stems and in 

leaves of trees are strongly related. Where higher concentrations occur in the stems, higher concentrations are 

also found in the leaves.

12. Tendencies in the concentrations of certain elements indicate that steins concentrate barium, calcium, 

copper, lead, and strontium; leaves concentrate aluminum, iron, magnesium, potassium, titanium, ytterbium, 

and zirconium; and that stems and leaves are approximately equal in their concentrations of boron, 

chromium, manganese, nickel, and phosphorus.

13. In the low-death-rate area of northern Georgia 

the concentration of most elements in tree samples tends 

to be higher than in the high-death-rate areas of 

Georgia. Therefore, trees appear to be more sensitive 

than vegetables to the variation in element content of 

soils from the two areas.

CONCLUSIONS

1. The greater abundance of many chemical elements 

in soils from the low-death-rate area (northern Georgia), compared with their abundance in soils from the 

high-death-rate areas (south-central Georgia), is believed to reflect the differences in the character of the 

bedrock which provided the materials for soil formation. The sediments in the high-rate area probably had 

been extensively weathered and leached during their 

original deposition. Soils formed on these sediments, 

consequently, are relatively deficient in many elemental 

constituents. The present soils in the low-death-rate 

area, on the other hand, are being continously supplied 

with elements from the weathering of fresh igneous and 

metamorphic rocks.

2. The analyses of tree samples and some vegetable 

samples tend to reveal the geochemical differences in 

soils from the two areas only when examined on a broad 

scale.

3. The difference between the two areas in the levels 

of various chemical elements present in vegetables appears to be so slight as to be unlikely to contribute appreciably to the observed differences in death rates in 

middle-aged humans. These data show that garden vegetables do not clearly reflect the chemical compositions 

of the soils on which the vegetables grew. The chemicals 

in soils, however, may enter the human food chain in 

water, in food plants that were not sampled in this 

study, and in meat and milk from animals that have fed 

on cultivated forage plants and native vegetation.

4. If geochemical differences between the two areas 

do, in fact, have a causal relationship to death from
GEOCHEMICAL ENVIRONMENTS, CARDIOVASCULAR MORTALITY RATES, GEORGIA

and leaves of trees in the high- and low-death-rate areas of Georgia

in the sample (steins or leaves) was beyond the range of measurement by the analytical methods that were used; -..., insufficient data]

C39

Sassafras Smooth sumac Sweetgum Black cherry

High-death- Low-death- High-death- Low-death- High-death- Low-death- High-death- Low-deathElement or ash rate area, rate area, rate area, rate area, rate area, rate area, rate area, rate area, 

17 pairs 27 pairs 30 pairs 30 pairs 28 pairs 27 pairs 30 pairs 30 pairs

TNrNrNrNrNrNrNrN

Al.. ------------------------------------- 0.75 0 0.70 0 0.69

Ash..-..---.------.--------------------.-. .43 0 .19 0 .38

B. ------.----.------------------------- .24 0 .35 0 .42

Ba. - ---.------ --..----...--. .69 0 .82 0 .73

Ca.... -------._-----__--...--..-..-... .75 0 .75 0 .72

Co. ---_.-------._-- .--._.-..._-..---_ 17 --_ -__ 27 ....--...

Cu._ -_. -.__.-..--.-....._-._--_ .73 0 .46 0 .53

Mg... .59 3 .59 2 .51

Ni. ......................................... .47 0 .57 0 .61

P...-. ..................................... .37 0 .64 0 .45

Pb - --.---..- ---_._-. .._-.___ -.16 0 .67 2 .69

Sr... ........... ....................... ...... .88 0 .88 0 .69

Tl R7 0 79 ft ft*

V. .....-.- ............-............... .54 13 .11 22 ..........

Zn. ............... .......................... .61 0 .50 0 .44

cardiovascular diseases, the cause would appear to be a 

deficiency, rather than an excess, of the elements that 

were studied.

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Carter, R. L., and Giddens, Joel, 1954, Soils of Georgia Their 

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Fernald, M. L., 1950, Gray's manual of botany [8th ed.] : New 

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Laurence, R. A., 1968, Ore deposits of the Southern Appalachians, p. 155-168, in Ridge, J. D., ed., Ore deposits of the 

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0 0.69 0 0.68 0 0.32 0 0.63 0 0.73 0 

0 .51 0 .60 0 .56 0 -.17 0 .43 0 

0 .40 0 .59 0 .33 0 .78 0 .25 0 

0 .890 .830 .660 .890 .94 0 

0 .56 0 .75 0 .87 0 . 69 0 .69 0 

30 ......... 30 .......... 26 .......... 27 .......... 30 .......... 30

0 .62 4 .25 0 .33 0 .44 2 .40 3 

0 .53 0 .91 0 .70 0 .33 0 .61 0 

0 .73 0 .64 0 .49 0 .57 0 .19 0 

0 .42 0 .83 0 .79 0 .58 0 .61 0 

3 .72 0 -.21 6 .56 3 .60 10 .39 6 

0 .82 0 .64 0 .74 0 .91 0 .81 0 

13 .68 11 .64 1 .89 0 .43 8 .54 9 

0 .52 0 .84 0 .57 0 .76 0 .66 0 

3 .59 1 .34 4 .56 1 -.07 7 .58 2 

0 .89 0 .84 0 .52 0 .74 0 .93 0 

0 .42 0 .54 0 .78 0 .61 0 .62 0 

28 ----.-.--- 28 . 28..... 27 .......... 29---------. 30

0 .61 0 .65 0 .57 0 -.39 0 .52 0

 1967b, Methods of computation for estimating geochemical abundance : U.S. Geol. Survey Prof. Paper 574-B, 15 p. 

Myers, A. T., Havens, R. G., and Duntoii, P. J., 1961, A spectrochemical method for the semiquantitative analysis of rocks, 

minerals and ores : U.S. Geol. Survey Bull. 1084-1, p. 207- 

229. 

Sauer, H. I., 1962, Epidemiology of cardiovascular mortality 

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465. 

Shacklette, H. T., and Sauer, H. I., 1964, The association of 

cardiovascular mortality rates in Georgia with the abundance and distribution of certain elements in rocks, soils, 

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Sutcliffe, J. F., 1962, Mineral salts absorption in plants: New 

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U.S. Geological Survey, 1968, Landforms of the United States: 

U.S. Geol. Survey painph., 15 p. 

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National Atlas of the United States of America : U.S. Geol. 

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Analytical methods used in geochemical exploration by the 

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statistical classification of diseases, injuries and causes of 

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U.S. GOVERNMENT PRINTING OFFICE: 1969 O 368-640