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Cardiovascular mortality in the southeastern United States: The coastal plain enigma
CARDIOVASCULAR MORTALITY IN THE SOUTHEASTERN UNITED STATES: THE COASTAL PLAIN ENIGMA MELINDA MEADE
Department
of Geography,
University of North Carolina, Chapel Hill, NC 27514, U.S.A.
Abstract-The spatial pattern of cardiovascular mortality in Alabama. Georgia, North and South Carolina has suggested that causative factors in the geochemical environment may be involved. Agestandardized mortality rates for sex and race subgroups of the population over two time periods. are used to examine the pattern. An optimal regression analysis indicates the divergent mortality associations of the groups. Canonical analysis is used to examine the linkages of mortality and socio-economic variable sets over time. Stress of change factors are indicated in explaining the mortality pattern and need to be included in any design to isolate influences of the geochemical environment.
INTRODUCTlON
For decades there have been unusually high death rates on the coastal plain of the southeastern United States for all causes of death, for some sites of cancer, and especially for cerebrovascular diseases (CVD). Of the 100 highest cardiovascular death rate counties, 89 are on the coastal plain and its geologic extension into the Mississippi Valley; 64 of the very highest are in Georgia and the Carolinas. The pattern was long masked by mapping at the state level. As the solid belt of counties with high CVD mortality became recognized in the 1950’s, the southeastern coastal plain became known as the “Enigma Area”. This research report analyzes the mortality structure and socioeconomic associations of that spatial pattern. BACKGROUND
Many risk factors and demographic associations are known for cardiovascular disease, Statistics show that incidence increases with age, is higher in men than women and has been declining for the past 20 years. Blacks and whites have similar incidence of arteriosclerotic heart disease, but blacks have higher incidence and mortality rates for stroke, and much higher rates of hypertension. The combined risk factors of cholesterol, blood pressure, type A personality, blood sugar and lack of exercise explain less than half of the demographic incidence pattern, and little of the spatial variation of incidence within the United States. The marked spatial variation in incidence of arteriosclerotic heart disease and stroke, especially on the international scale, has long been considered etiologitally significant. Numerous studies have been conducted oil comparative life styles. diet, genetic predisposition and similar factors which have been used to substantiate or challenge laboratory findings and animal model studies [l]. As new standardized procedures are developed for measuring such things as blood pressure. there is renewed interest in the geographical variation within this country [Z]. Perhaps the most important current research is concerned with understanding the reasons for the dramatic de257
cline in cardiovascular mortality since 1970, both nationally and with special impact upon the Southeast. It has seemed to many health researchers that the limits of the Enigma Area are so coincident with the fall line that a physical environmental factor is strongly suggested. Geochemical differences between the coastal plain and the Piedmont include not only water hardness, but coastal trace element deficiencies in zinc, ~~esium, selenium, and other elements essential in the biochemistry of blood clotting and cholesterol metabolism. This evident pattern lends itself to simplistic abuse. Soil chemistry must be translated into forage and food crop uptake, internal distribution and storage of elements, and the elements then passed through food preparation and cooking. National marketing systems today affect even the most rural of counties. It is difficult, therefore, to establish direct links between the local soils of the coastal plain growing peanuts, cotton and tobacco and local human food chains over an extensive area. It is especially difficult to do so for the high death rate cities of the coastal plain, Savannah and Charleston. Water seems a plausible influence, but the Enigma Area draws upon several artesian aquifers as well as a variety of interspersed surface and well waters. Furthermore, water composition changes considerably as it passes through processing and piping, and trace elements interact synergistically or in blocking actions poorly understood in human physiology [3]. The framework for water sampling is crude and inconsistent in both scale and periodicity. A few careful, preliminary studies of the spatial patterns have been done [4]. More commonly, regional intercorrelations have resulted in gross associations. National cardiovascular mortality, for example, has been statistically associated with such factors as humidity, warm January isotherm, (inverse) continental climate, low industrialization and Baptist religion, because of the influence of the Enigma Area on national mortality levels. The characteristics pi’ the coastal plain have influenced settlement pattern, agricuhural systems, types of manufacturing. standards of living and other
MELINDA MEADE
258
factors of the socio-economic environment which underly life stress, occupational exposures, physical activity, health services and rates of change. The effect of the environment on cardiovascular mortality may therefore be entirely indirect. Detailed fieId studies are needed to trace the interactions between soil and water chemistry and population exposure and behavior if geochemical associations are to be supported or refuted, but if any hypotheses are to be tested the socio-economic influences must be controlled first. As a first step, the Enigma Area must be better defined and the explanation offered by socio-economic factors considered. It is generally considered today that chronic, degenerative diseases need to be studied through a multiple cause, multiple effect model. Many substances and behaviors may cause cancer or cardiovascular disease, and the effect of a single substance or behavior may become manifest in a variety of sites or conditions according to individual response. This study treats the cardiovascular diseases, i.e. ischemic heart disease, stroke, and hypertension without renal involvement, as a group (ICDA 390-448, 780-796). It is the beginning of an attempt ultimately to build an ecological model of CVD causation, and immediately to develop a framework for identifying criteria and sites for in-depth, microlevel field study which may generate new hypotheses and perspectives. SPATIAL
PATTERNS
OF MORTALlTY
The Enigma Area has been defined as a region by the criterion of high CVD mortality. The persistence of the region over time, its identity among sex and race subdivisions of the population and its internal structural differentiation, have not been explicitly addressed. Socio-economic factors in particular are
different for population subgroups, a differentiation lost when working with total mortality. This study utilizes race and sex specific, directly age-adjusted CVD mortality rates for the counties of Alabama, Georgia, North and South Carolina refined by adjusting for resident institutional populations [S]. Mortaiity is averaged over a period of years, 1958-1961 and 1968-1972, in order to stabilize the fluctuations associated with small populations. Six to ten mountain counties with negligible black male or female populations, out of 372 counties, still show extreme rates evident in the maps. They were not dropped. Mortality rates were mapped at county level. The Enigma Area is best delimited by the rates for white males, 1959-1961, mapped against the range of total cardiovascular mortality (Fig. 1). When white male mortality is mapped against its own range of rates, the area becomes markedly less solid, but still recognizable (Fig. 2). The region is fess differentiated for white females (Fig. 3), and can be said not to be a region of high death at all for blacks (Figs 4 and 5). High death rate counties occur throughout the piedmont and low rate counties on the coastal plain, although the mountain counties continue to show low rates overall, with scattered extreme rates resulting from a few deaths in very small (black) populations. Rather than a clear coastal plain/Piedmont and mountain regionalization, the most common pattern involves high death rates in South Carolina. This is emphasized when distribution over time is considered. By 1968-72, CVD mortality for black females and other subgroups has declined greatly in absolute terms, and has become more concentrated in South Carolina (Fig. 6). The Enigma Area is a region of high white CVD mo$ality. Whereas black CVD rates in the Southeast are elevated compared with national rates, their with-
Fig. 1. White male cardiovascular mortality in four states of the Southeast, 19594961, compared to the range for ail population groups.
Cardiovascular
Fig. 2. White male cardiovascular
mortality in the southeastern
United States
259
mortality in four states of the Southeast, 1959-1961, within the range for white males only.
in-region distributional pattern is dissimilar to that of white rates. They thus pose a challenge to the geochemical hypotheses. The so&o-economic associations of mortality may be determinate. SOCIOECONOMIC ASSOCIATIONS
There is considerable evidence that ’ “stress” increases the risk of CVD. That it is an amorphous factor whose definitions and surrogate measures are
Fig. 3. White female cardiovascular
legion does not diminish its importance as a link between the social environment and the biophysical pathways of human adaptability. Stressors act not directly as pathogens, but as symbols indirectly affecting endocrine systems [q. The diversity of the reactions of individual human beings to specific stressors has confounded many studies of direct, simple causation and emphasized the need for multiple cause/multiple effect explanations.
mortality in four states of the Southeast, 1959-1961.
260
MELINDA MEADE
Fig. 4. Nonwhite male cardiovascular mortality in four states of the Southeast, 1959-1962. Studies involving psycho-social approaches to stress may generally be classified into one of two groups. The first is concerned with the stress induced by change itself, by the need for social adaptation and alteration of individual values or personality integration. These studies range from accounts of the impact of bad news or the crisis of divorce to broader studies of the effects of recent industrialization and of social disorganization [7]. The other focuses upon the stress
induced by low socioeconomic status, discrimination, living conditions, and despair as reflected in variables measuring housing quality, crowding, or simply poverty [S]. These indicators have been previously associated with infant mortality and homicide and alcoholism. In addition, population characteristics and dynamics are themselves sometimes used directly, especially by geographers. The age structure of the population, racial composition and sex ratio often are
29300 - 36623 21975 - 29300 14650 - 21975 7325 - 14650 n
0 - 7325
DEATHS PER MlLLlON
Fig. 5. Nonwhite female cardiovascular
mortality in four states of the Southeast. 1959-1961
Cardiovascular mortality in the southeastern
Fig. 6. Black female cardiovascular
261
rnorta~~t~ in four states of the Southeast, 19%1961.
the most strongly related variables [9]. Although useful for planning purposes, such variables do not in themselves “explain” anything except the need for age/sex/race specific mortality rates. Additional factors which plausibly affect the spatial variation in CVD are diet, health care and bias in ~rtifi~tion of death. Dietary variations at the international and individual scales have been consistently related to CVD, especially to arteriosclerosis, At the scale of inter-county variation within the United States, however, the importance is doubtful and almost impossible to measure. Briggs and Leonard used percent of foreign born population, which in Ohio might be a reasonabie diet indicator but in the Southeast is most likely to be a surrogate for size of central place [to]. With the exception of develop ments in hypertension control too recent to have affected the period under study, health care is probably most important as an environmental factor acting together with housing and community conditions to produce stress by its deficiency. It acts as well upon the overall strength and health status of individuals, and in this regard needs to be included in some direct manner in future studies. Bias in certification of death resulting from incompleteness, fad, method of choosing coroners, or medical school influence over certain areas would be serious for any effort at analysis. Studies of this matter, however, have found such differences account for only a small percentage of differences in CVD mortality [I 11. OPTIMAL
United States
REGRESSION
One may view a disease state as the resolution of interactions between environmental stressors, popuiation characteristics and cultural behavioral patterns. It is apparent from the literature and from the differ-
ent spatial distribution of CVD that psycho-social stressors affect the population subgroups differently. Smoking, exercise and diet are difficult behavior to measure at the county scale, and are not estimated although they certainly differ by race and sex. Instead, activity levels are approached by the usual measures of types of economic activity, and income is used as a surrogate for the behavior of different lifestyles. Data are from the 1962 and 1972 County and City Data Book. Variables are selected to represent the demographic, social, and developmental change dimensions of the r&o-economic environment (Table 1). The major research hypotheses were: (1) that black mortality would be associated with measures of poor environment and status: income level, poor housing and plumbing, high density, and black migration; (2) that white mortality would be associated, especially in the earlier period, with measures of economic development: farmers working off the farm, educational levels, urban living, retailing and managerial/ professional employment; (3) that male mortality would be more related, in both races, to economic change and female to poor environment; (4) that a measure of population change would be the single most important variable for all groups; and (5) that the explanation for 1968-1972 mortality regressed on 1962 socio-economic data would be stronger than for its regression on 1972 socio-economic data. The models tested were slightiy different for the dependent mortality variables. A table of intercorrelations was used to select the best representative variables for each model, in order to reduce evident multicollinearity. Some data available for 1972 also
262
MELINDAMEAUE Table 1. Optional regression results Cardiovascular
mortality
1968-1972 White Variables “, Population change “/, Population change Median age “/, Foreign born 9/, Migration S’, Change black population Economic developments “/;1Urban Median education % Labor in retailing ?, Labor in manufacturing Y/,Labor in government ‘% Labor managerial/professional % Farmers working 100 days off farm ‘?/,Change farm land % Change in value added Status and conditions Median family income 9’, Low income (poverty) % Low farm income ‘Z, Old housing
‘T’,poor plumbing % Room density over 1.06 Density Y, Land in farms % Budget spent on health R2 Four variable model
No. variables entered in model R2 CompIete model
1958-1961 White
Black
Females
Males
Females
Males
1
+
-
+
+
2
*3 X -
2 X + *1
;: X
X
3 + X + 4 X
Males
Nonwhite
Females
Males
Females
+
+
-
*1 3 X X
*1 ; X
2 X X
+ + 2 + + +
+ 4 X + ;
+ + + + + +
4 X X
1
;: X
; x
+ + 3 X X 4
1 + ; + 2 4 X
;
+ X
l4
;
+
X X
+ +
X X
X
x
-
+
X
X
X
X
X X +
X x +
4 X
+
+ + + 3
+ + x
+ 2 3
-
;
;
X
1:
+
+ X + +
+ x x +
3 -
+ +
+ +
2
x’
22.6 13 30.4
13.9 13 18.0
4.0 15 8.0
30.9 16 34.3
‘1 X -
;
;
-
3 X
-
I
2
4
+
x’
x’ X
; X
X X
10.5 19 23.4
19.0 12 16.2
14.1 16 19.8
7.7 12 8.2
l
* Indicates best one variable, whether retained in model or not. 1, 2, 3. 4, indicates position in four-variable model. + Indicates statistical significance and inclusion in model. - Indicates statistically not significant at 0.5 entry level. X Indicates variable not considered in model.
were not available for 1962. The results are shown. in a rather unconventional manner, in Table 1. More detailed information is not presented due to the complexity of the models, and to the preliminary purposes of this stage of the analysis. Population change is indeed important, except for black male CVD mortality 1968-72. The great importance of median age of the population for these agestandardized rates may lie in its reflection of past population change. There is a tendency for white mortality to be more associated with economic development and black with poor conditions, especially for the earlier period. The most important measures of change for whites is the percentage of farmers working 100 days or more off the farm, which is reflective of the rural population now commuting to factory jobs but not moving to cities. The pattern of relations between the sexes is rather confused. The most striking development is the emergence of similarly high degrees of explanation for white male and black ferntile, and the loss of explanation for black male CVD mortality. The results of the lagged regression are not shown for reasons of space. All of the model
explanations are much weaker using 1962 than 1972 socio-economic data for 1968-72 mortality. The most important variables are similar to those for the 1958-61 mortality associations. CANONICALANALYSIS Even the use of multiple regression techniques is reductionist when the need is to analyze multiple cause/multiple effect relations. Variables were deleted because of multicollinearity, for example, whereas it is probable that their effects are synergistic. The research problem is to examine the association of the entire ser of sock-economic conditions with the entire set of CVD mortality results and to compare the structure of relations over time. Canonical correlation analysis involves the creation of the linear combination of X set variables and the linear combination of Y set variables such that the resultant canonical variates are maximally correlated. More than one set of linear combinations may be highly correlated, yielding several cannonical variates (factors). The major assumptions are linearity of rela-
Cardiovascular
mortality in the southeastern
variables and sets of variables, and for purposes of statistical testing, normal distribution. The inter-relations of variables are not a problem, as they are incorporated into the derivation of standard weights which create the variates. Multicollinearity does become a problem in the interpretation of the variable coefficients, however, and has led to the use of correlations between the original variables and the canonical variate as the canonical “loadings” [ 121. Measures of “redundancy” indicate explained variance, and the squared loadings for each variate divided by the number of variables yields the proportion of the variance in the variable set accounted for by a variate.* The sets of sex and race specific mortality data for 1958-1961 and 1968-72 are the dependent variables, and the sets of so&-economic variabtes for 1962 and 1972 the independent. After analyzing the regression results, it was hypothesized that the mortality experience of white males and black females would load together on a factor of economic hope, that there would be a rural poverty factor, and that the races rather than the sexes would separate on factors representing different environmental conditions. It was expected that the overall explanation would improve over time, and that a lagged canonical correlation would be weaker. The results are shown in Table 2. Total explanation (redundancy) increases from 20.3% to 27.2%. This is largely due to the associations of white male mortality. CVD death rates for black females and white males do load together, but hardly on a factor of tions among
l The interpretation of canonical variates and the derivation of redundancy, variation extracted, canonical Ioadings, canonical coefficients, and canonical variates are explained in Briggs and Leonard [9], Levine [12] and Cooley and Lohnes [13].
United States
263
hope: the associations in 1972 are with population change and room density, poverty, poor housing. In 1962, they are related oppositely to measures of income and environment. Whites are similarly related in both 1952 and 1972 to measures of change, but black male CVD mortality is more independent from black female. Black rates load together most in relation to income and education. “Working off the farm” is important mainly (and inversely} for males in 1962. Education, income, urbanization (urban, migration, black population change), working off the farm-in short, the stresses of development-emerge as strongest variables in 1972. Poverty is clearly important, but no rural poverty factor is easily differentiated from urban poverty. As expected, the lagged canonical cqrrelation of 1968-72 mortality and 1962 socio-economic data is weak, with total redundancy a mere 14%.
SUMMARY
DlSCUSSION
The complex variable relations and set linkages revealed by the canonical correlation analysis suggest numerous enigmas. Description, explanation, and speculation could occupy many pages. It is interesting to reverse the perspective, however, and note that all the so&-economic variables in combination “explain” only 20-30*% of the CVD mortality variance by county. The proportion is slightly more for white males and black females, and considerably less for black males. The socio-economic variables become more important with time, as development and change intensify, and are most important for the subgroup of the population that has been most involved in so&-economic development. These results suggest that there may indeed be an underlying physical environmental factor being increasingly submerged by the gathering stresses of so&-economic change. This
LEGEND l 1.1to 2.0 greater than -1.1 to -2.0 greater
2.0
than -2.0
UP Canonical
Variate Voriote
Fig. 7.
Scores 1
Canonical variate scores for the mortality set, variate 1 of the 1972 canonical correlation.
Totai redundancy for 1968-72 CVD Mortality All canonical correlations highly significant.
0.4268 0.2019 74.02, 0.6885
Trace variance extracted Variant redundancy Proportion of total redundancy Canonical correlation coefficient
0.2239 0.0255 9.5:; 0.3879
-0.3248 0.7183 0.4923 0.1783
0.03 I7
-0.2253
0.023 0.100 0.089 0.057 0.054 0.074
-0.1130 -0.0455 - 0.0672 0.1060 -0.0188 -0.0138 0.2658 0.2101 0.0001 0.1317 - 0.0082
correlation
CVD
0.2239 0.0520 25.676 0.4820
-0.7363 -0.1030 0.4180 -0.4100
0.0438
-0.3788
0.0536 - o.ooo7
for 19.58-61
0.3953 0.1207 59.40/, 0.5525
0.3418 0.7216 0.6445 0.7268
0.0555
0.4491
0.1286 0.2401
0.6613 0.0102 - 0.0034 0.3214 -0.0120 -0.1569 -
- 0.0679 0.0910 -0.0525 0.0905 -0.0234 -0.1049
-0.6885 0.1466 - 0.0636 -0.1253 0.1844 -0.0162 0.0612 0.0304 -0.0442 -0.1004 - 0.0072 0.3192
- 0.0866 -
0.0066
(32
Canonical
-0.0117
0.0078
0,
results
total redundancy
33.7 13.0 18.2 35.1
7.3
1.4 6.3 5.6 3.6 3.4 4.7 3.6 3.5 3.1 3.2 2.5
5.7 7.9 8.0 15.3 0.6 2.3 5.5 2.4 3.1 1.0
lOORf/ZR:
redundancy
data = 0.2719;
0.367 0.141 0.198 0.382
0.116
0.056 0.049 0.051 0.039
0.058
0.091 0.126 0.127 0.244 0.010 0.036 0.087 0.038 0.050 0.016
Rf
Variable
2. Canonical
-0.1529 -0.1864 0. I347 -9.3223 0.2154 -0.1798 -0.1439 0.2695 -0.0625 -0.3578
CV,
given 1972 socio-economic
0.1869 0.0445 16.5% 0.4879
0.531 I 0.4428 -0.1017 -0.5092
0.7799 0.2743 0.5955 0.8179
0.5344
- 0.2999 0.1548
0.2972 0.6456 -0.5584 -0.4148 -0.4685 -0.1979 0.35oI 0.3709 -0.3247 -0.3197 -0.1835
- 0.0208 - 0.0379 0.1741 0.1752 0.0567 0.3687 0.2097 0.1955 0.2223 0.2310 0.2566
0.0670
0.5201 0.5274 0.439 1 0.2489 -0.1176 0.3697 0.5973 0.2022 0.1307 0.0568
-0.2251 -0.3445 0.4096 0.6172 - 0.0524 0.0067 0.0085 -0.2065 0.3115 -0.0275
CVZ
loadings
Trace variance extracted Mortality variables Black (nonwhite) females Black (nonwhite) males White females White males
Socio-economic variables “1 Change population O’ Migration “1 Urban q0 Change black population Median age “/;, Foreign born Median education y0 Labor in manufacturing ‘?/, Labor in retailing Y’, Labor in government ’ 0’ Labor in professional/ managerial Median family income “/;, Poverty income H; Old housing /0 Inadequate plumbing ‘?; Room density > 1.06 7; Budget/Health :d Change value added “/, Low farm income “/, Change farm land % Land in farms % Farmers working 100 days off farm
CV,
Canonical
1972 Variates
Table
Mortality
0.1799 0.0155 7.6”‘;) 0.2940
0.5344 0.3941 0.0486 -0.5257
0.1962
-0.3663
0.385 I 0.2636
- 0.4489 0.7331 - 0.7482 0.4437 0.5436 -0.5909
0.2868 0.3144 0.6119 0.4983 0.1585 0.1535
0.0159
0.0261
cv3
loadings
0.336 0.201 0.198 0.226
0.112
0.026 _.
0.120 0.052 0.054 0.027 0.068 .-
0.157 0.029 0.035 0.054 0.014 0.007
0.002
0.008 -
data = 0.2031.
35.0 20.9 20.6 23.5
13.4
3.0 3.1 _
.__
14.4 6.2 6.5 5.4 3.2 8.1
18.8 3.5 4.2 6.5
0.2
1.0 -
Variable redundancy Rf lOOR,2/ER’
given 1962 socio-economic
0.2010 0.0149 7.37,; 0.2127
0.2353 -0.5598 0.6388 0.1651
0.0652
0.2599
0.2857 0.1611
-..
- 0.0556 -0.2592 0.2493 0.1009 -0.1380 0.0595
- 0.2304 0.4009 0*1018 -0.5906 0.1098 0.2496
0.0888
0.3279 -
cv4
1962 Variates
E
Cardiovascular
mortality in the southeastern
United States
265
somewhat
counters the skepticism induced by the disparate spatial mortality pattern of the population subgroups. The pattern of canonical variate scores, however, invariably mirrors the mortality dichotomy between coastal plain and mountains. One example of this is presented in Fig. 7. It is thus the Enigma Area death rates that best are explained by the socio-economic analysis, and the intermediary, dynamic piedmont zone that is most problematic. Clearly, socio-economic factors must be included along with physical environmental factors in the frame for any research design. A typology based on canonical variate scores would be invaluable to classifying and selecting counties on a comparative basis for in-depth field study.
Georgia. U.S. Geol. Surv. Prof. Paper No. 574-C. U.S. Govt. Printing Office, Washington, D.C. 1970. 5. Sauer H. I. Descriptive associative methodology. In Geochemistry and the Environment, Vol. -III, p. 121. National Acad. Sci. Washington, D.C., 1978. 6. Camel J. The contribution of the social environment to host resistance. Am. J. Epidem. 104, 109, 1976. 7. Cassel J. The contribution of the social environment to host resistance. Am J. Epidem. 1Oq 109, 1976; Tassel J. and Tyroler H. A. Epidemiologic study of cultural change, health status and the recency of-industrialixation. Archs Enuir Hlth 3. 25. 1961: James S. A. and Kleinbaum D. G. Socioeconomic stress and hypertension related mortality rates in North CarolinaI‘Am. J. oubt. Hlth 66. 354. 1976: Neser W. B.. Tvroler H. A. * and Cassell J. C. Social disorganization and stroke mortality in the black population of North Carolina.
Acknowledgement-The cardiovascular mortality data used in this study were developed and refined by Herbert I. Sauer after years of experience and are invaluable to further study.
8. Briggs R. and Leonard W. A. IV. Mortality and ecolog&d structure: a canonical approach. Sot. Sci. Med. 11.757, 1977; Kotchen J. M. and Kotchen T. A. Geographic effect on racial blood pressure differences in adolescents. J. Chron. Dis. 31, 581, 1978; Robert R. E., McBee G. W. and MacDonald E. F. Social status, ethnic status and urban mortality: an ecological approach. Tex. Rep. Biol. Med. 28, i3, 1970; Wilt& D. M.. Walklev R. P.. Pinkerton T. C. and Yavback M. The Ho&9 Environment and Family Life: *A Longi-
Am. J. Epidem.
REFERENCES Jolliffe N. and Archer M. Statistical associations between international coronary heart disease death rates and certain environmental factors. J. Chron. Dis. 9,636, 1959; McGill H. C. Jr. Geographic Pathology of Artherosclerosis. Lea and Febiger, Philadelphia. 1958; Keys A. (Ed.) Coronary heart discasc in seven countries. Circulation 41, 1970, suppl. I; Kagan A. et al. Epidcmiologic studies of coronary heart disease and stroke in Japanese men living in Japan, Hawaii, and California: demographic, ph&ical, -dietary, and biochemical characteristics. J. Chron. Dis. 27. 345. 1974. Kotchen J. and Kotchen T. A. Geographic effect on racial blood pressure differences in adolescents. J. Chron Dis. 31, 581, 1978. Angino E. A. et al. Water: trace elements in solution. In Geochemistry and the Environment, Vol. 111, p. 32. National Acad. of Sciences, Washington, DC., 1978. Sauer H. I. Counties with extreme death rates and associated factors. Am. J. Epidem. 99,258, 1974; Sauer H. I., Payne G. H., Council C. R. and Terre11 J. C. Cardiovascular disease mortality patterns in Georgia and North Carolina. Pub/. HIth Rep. 81, 455, 1966; Schacklette H. T., Sauer H. I. and Miesch A. T. Geochemical environments and cardiovascular mortality rates in
tudinal Mental
93, 166, 1971.
Study o/the Effects of Housing on Morbidity Health. Johns Hopkins Press, Baltimore,
and
1962. 9. Briggs R. and Leonard W. A. IV. Mortality and ecolo&al structure: a canonical approach. Soi Sci. Med. 11, 757, 1977; Pyle G. F. Heart Disease, Cancer and Stroke in Chicago. University of Chicago, Department of Geography research paper no. 134,ChicaRo, 1961; Robinson V. B. Modeling spatial variations in heart disease mortality: impl&ions of the variable subset selection process. Sot. Sci. Med. 12D. 165, 1978. 10. Briggs and Leonard, op cit. 11. Kuller L. H. et al. Nationwide cerebrovascular disease mortality study III. Accuracy of the clinical diagnosis of cerebrovascular disease. Am. J. Epidem. 90, 556, 1969.
12. Levine M. S. Canonical Analysis and Factor Comparison. Sage University paper series on Quantitative Analysis in the Social Sciences, series no. 07-006. Sage Publications, Beverly Hills and London, 1977. Data 13. Cooley W. W. and Lohnes P. R. Multivariate Analysis. Wiley, New York, 1971.
Department
of Geography,
University of North Carolina, Chapel Hill, NC 27514, U.S.A.
Abstract-The spatial pattern of cardiovascular mortality in Alabama. Georgia, North and South Carolina has suggested that causative factors in the geochemical environment may be involved. Agestandardized mortality rates for sex and race subgroups of the population over two time periods. are used to examine the pattern. An optimal regression analysis indicates the divergent mortality associations of the groups. Canonical analysis is used to examine the linkages of mortality and socio-economic variable sets over time. Stress of change factors are indicated in explaining the mortality pattern and need to be included in any design to isolate influences of the geochemical environment.
INTRODUCTlON
For decades there have been unusually high death rates on the coastal plain of the southeastern United States for all causes of death, for some sites of cancer, and especially for cerebrovascular diseases (CVD). Of the 100 highest cardiovascular death rate counties, 89 are on the coastal plain and its geologic extension into the Mississippi Valley; 64 of the very highest are in Georgia and the Carolinas. The pattern was long masked by mapping at the state level. As the solid belt of counties with high CVD mortality became recognized in the 1950’s, the southeastern coastal plain became known as the “Enigma Area”. This research report analyzes the mortality structure and socioeconomic associations of that spatial pattern. BACKGROUND
Many risk factors and demographic associations are known for cardiovascular disease, Statistics show that incidence increases with age, is higher in men than women and has been declining for the past 20 years. Blacks and whites have similar incidence of arteriosclerotic heart disease, but blacks have higher incidence and mortality rates for stroke, and much higher rates of hypertension. The combined risk factors of cholesterol, blood pressure, type A personality, blood sugar and lack of exercise explain less than half of the demographic incidence pattern, and little of the spatial variation of incidence within the United States. The marked spatial variation in incidence of arteriosclerotic heart disease and stroke, especially on the international scale, has long been considered etiologitally significant. Numerous studies have been conducted oil comparative life styles. diet, genetic predisposition and similar factors which have been used to substantiate or challenge laboratory findings and animal model studies [l]. As new standardized procedures are developed for measuring such things as blood pressure. there is renewed interest in the geographical variation within this country [Z]. Perhaps the most important current research is concerned with understanding the reasons for the dramatic de257
cline in cardiovascular mortality since 1970, both nationally and with special impact upon the Southeast. It has seemed to many health researchers that the limits of the Enigma Area are so coincident with the fall line that a physical environmental factor is strongly suggested. Geochemical differences between the coastal plain and the Piedmont include not only water hardness, but coastal trace element deficiencies in zinc, ~~esium, selenium, and other elements essential in the biochemistry of blood clotting and cholesterol metabolism. This evident pattern lends itself to simplistic abuse. Soil chemistry must be translated into forage and food crop uptake, internal distribution and storage of elements, and the elements then passed through food preparation and cooking. National marketing systems today affect even the most rural of counties. It is difficult, therefore, to establish direct links between the local soils of the coastal plain growing peanuts, cotton and tobacco and local human food chains over an extensive area. It is especially difficult to do so for the high death rate cities of the coastal plain, Savannah and Charleston. Water seems a plausible influence, but the Enigma Area draws upon several artesian aquifers as well as a variety of interspersed surface and well waters. Furthermore, water composition changes considerably as it passes through processing and piping, and trace elements interact synergistically or in blocking actions poorly understood in human physiology [3]. The framework for water sampling is crude and inconsistent in both scale and periodicity. A few careful, preliminary studies of the spatial patterns have been done [4]. More commonly, regional intercorrelations have resulted in gross associations. National cardiovascular mortality, for example, has been statistically associated with such factors as humidity, warm January isotherm, (inverse) continental climate, low industrialization and Baptist religion, because of the influence of the Enigma Area on national mortality levels. The characteristics pi’ the coastal plain have influenced settlement pattern, agricuhural systems, types of manufacturing. standards of living and other
MELINDA MEADE
258
factors of the socio-economic environment which underly life stress, occupational exposures, physical activity, health services and rates of change. The effect of the environment on cardiovascular mortality may therefore be entirely indirect. Detailed fieId studies are needed to trace the interactions between soil and water chemistry and population exposure and behavior if geochemical associations are to be supported or refuted, but if any hypotheses are to be tested the socio-economic influences must be controlled first. As a first step, the Enigma Area must be better defined and the explanation offered by socio-economic factors considered. It is generally considered today that chronic, degenerative diseases need to be studied through a multiple cause, multiple effect model. Many substances and behaviors may cause cancer or cardiovascular disease, and the effect of a single substance or behavior may become manifest in a variety of sites or conditions according to individual response. This study treats the cardiovascular diseases, i.e. ischemic heart disease, stroke, and hypertension without renal involvement, as a group (ICDA 390-448, 780-796). It is the beginning of an attempt ultimately to build an ecological model of CVD causation, and immediately to develop a framework for identifying criteria and sites for in-depth, microlevel field study which may generate new hypotheses and perspectives. SPATIAL
PATTERNS
OF MORTALlTY
The Enigma Area has been defined as a region by the criterion of high CVD mortality. The persistence of the region over time, its identity among sex and race subdivisions of the population and its internal structural differentiation, have not been explicitly addressed. Socio-economic factors in particular are
different for population subgroups, a differentiation lost when working with total mortality. This study utilizes race and sex specific, directly age-adjusted CVD mortality rates for the counties of Alabama, Georgia, North and South Carolina refined by adjusting for resident institutional populations [S]. Mortaiity is averaged over a period of years, 1958-1961 and 1968-1972, in order to stabilize the fluctuations associated with small populations. Six to ten mountain counties with negligible black male or female populations, out of 372 counties, still show extreme rates evident in the maps. They were not dropped. Mortality rates were mapped at county level. The Enigma Area is best delimited by the rates for white males, 1959-1961, mapped against the range of total cardiovascular mortality (Fig. 1). When white male mortality is mapped against its own range of rates, the area becomes markedly less solid, but still recognizable (Fig. 2). The region is fess differentiated for white females (Fig. 3), and can be said not to be a region of high death at all for blacks (Figs 4 and 5). High death rate counties occur throughout the piedmont and low rate counties on the coastal plain, although the mountain counties continue to show low rates overall, with scattered extreme rates resulting from a few deaths in very small (black) populations. Rather than a clear coastal plain/Piedmont and mountain regionalization, the most common pattern involves high death rates in South Carolina. This is emphasized when distribution over time is considered. By 1968-72, CVD mortality for black females and other subgroups has declined greatly in absolute terms, and has become more concentrated in South Carolina (Fig. 6). The Enigma Area is a region of high white CVD mo$ality. Whereas black CVD rates in the Southeast are elevated compared with national rates, their with-
Fig. 1. White male cardiovascular mortality in four states of the Southeast, 19594961, compared to the range for ail population groups.
Cardiovascular
Fig. 2. White male cardiovascular
mortality in the southeastern
United States
259
mortality in four states of the Southeast, 1959-1961, within the range for white males only.
in-region distributional pattern is dissimilar to that of white rates. They thus pose a challenge to the geochemical hypotheses. The so&o-economic associations of mortality may be determinate. SOCIOECONOMIC ASSOCIATIONS
There is considerable evidence that ’ “stress” increases the risk of CVD. That it is an amorphous factor whose definitions and surrogate measures are
Fig. 3. White female cardiovascular
legion does not diminish its importance as a link between the social environment and the biophysical pathways of human adaptability. Stressors act not directly as pathogens, but as symbols indirectly affecting endocrine systems [q. The diversity of the reactions of individual human beings to specific stressors has confounded many studies of direct, simple causation and emphasized the need for multiple cause/multiple effect explanations.
mortality in four states of the Southeast, 1959-1961.
260
MELINDA MEADE
Fig. 4. Nonwhite male cardiovascular mortality in four states of the Southeast, 1959-1962. Studies involving psycho-social approaches to stress may generally be classified into one of two groups. The first is concerned with the stress induced by change itself, by the need for social adaptation and alteration of individual values or personality integration. These studies range from accounts of the impact of bad news or the crisis of divorce to broader studies of the effects of recent industrialization and of social disorganization [7]. The other focuses upon the stress
induced by low socioeconomic status, discrimination, living conditions, and despair as reflected in variables measuring housing quality, crowding, or simply poverty [S]. These indicators have been previously associated with infant mortality and homicide and alcoholism. In addition, population characteristics and dynamics are themselves sometimes used directly, especially by geographers. The age structure of the population, racial composition and sex ratio often are
29300 - 36623 21975 - 29300 14650 - 21975 7325 - 14650 n
0 - 7325
DEATHS PER MlLLlON
Fig. 5. Nonwhite female cardiovascular
mortality in four states of the Southeast. 1959-1961
Cardiovascular mortality in the southeastern
Fig. 6. Black female cardiovascular
261
rnorta~~t~ in four states of the Southeast, 19%1961.
the most strongly related variables [9]. Although useful for planning purposes, such variables do not in themselves “explain” anything except the need for age/sex/race specific mortality rates. Additional factors which plausibly affect the spatial variation in CVD are diet, health care and bias in ~rtifi~tion of death. Dietary variations at the international and individual scales have been consistently related to CVD, especially to arteriosclerosis, At the scale of inter-county variation within the United States, however, the importance is doubtful and almost impossible to measure. Briggs and Leonard used percent of foreign born population, which in Ohio might be a reasonabie diet indicator but in the Southeast is most likely to be a surrogate for size of central place [to]. With the exception of develop ments in hypertension control too recent to have affected the period under study, health care is probably most important as an environmental factor acting together with housing and community conditions to produce stress by its deficiency. It acts as well upon the overall strength and health status of individuals, and in this regard needs to be included in some direct manner in future studies. Bias in certification of death resulting from incompleteness, fad, method of choosing coroners, or medical school influence over certain areas would be serious for any effort at analysis. Studies of this matter, however, have found such differences account for only a small percentage of differences in CVD mortality [I 11. OPTIMAL
United States
REGRESSION
One may view a disease state as the resolution of interactions between environmental stressors, popuiation characteristics and cultural behavioral patterns. It is apparent from the literature and from the differ-
ent spatial distribution of CVD that psycho-social stressors affect the population subgroups differently. Smoking, exercise and diet are difficult behavior to measure at the county scale, and are not estimated although they certainly differ by race and sex. Instead, activity levels are approached by the usual measures of types of economic activity, and income is used as a surrogate for the behavior of different lifestyles. Data are from the 1962 and 1972 County and City Data Book. Variables are selected to represent the demographic, social, and developmental change dimensions of the r&o-economic environment (Table 1). The major research hypotheses were: (1) that black mortality would be associated with measures of poor environment and status: income level, poor housing and plumbing, high density, and black migration; (2) that white mortality would be associated, especially in the earlier period, with measures of economic development: farmers working off the farm, educational levels, urban living, retailing and managerial/ professional employment; (3) that male mortality would be more related, in both races, to economic change and female to poor environment; (4) that a measure of population change would be the single most important variable for all groups; and (5) that the explanation for 1968-1972 mortality regressed on 1962 socio-economic data would be stronger than for its regression on 1972 socio-economic data. The models tested were slightiy different for the dependent mortality variables. A table of intercorrelations was used to select the best representative variables for each model, in order to reduce evident multicollinearity. Some data available for 1972 also
262
MELINDAMEAUE Table 1. Optional regression results Cardiovascular
mortality
1968-1972 White Variables “, Population change “/, Population change Median age “/, Foreign born 9/, Migration S’, Change black population Economic developments “/;1Urban Median education % Labor in retailing ?, Labor in manufacturing Y/,Labor in government ‘% Labor managerial/professional % Farmers working 100 days off farm ‘?/,Change farm land % Change in value added Status and conditions Median family income 9’, Low income (poverty) % Low farm income ‘Z, Old housing
‘T’,poor plumbing % Room density over 1.06 Density Y, Land in farms % Budget spent on health R2 Four variable model
No. variables entered in model R2 CompIete model
1958-1961 White
Black
Females
Males
Females
Males
1
+
-
+
+
2
*3 X -
2 X + *1
;: X
X
3 + X + 4 X
Males
Nonwhite
Females
Males
Females
+
+
-
*1 3 X X
*1 ; X
2 X X
+ + 2 + + +
+ 4 X + ;
+ + + + + +
4 X X
1
;: X
; x
+ + 3 X X 4
1 + ; + 2 4 X
;
+ X
l4
;
+
X X
+ +
X X
X
x
-
+
X
X
X
X
X X +
X x +
4 X
+
+ + + 3
+ + x
+ 2 3
-
;
;
X
1:
+
+ X + +
+ x x +
3 -
+ +
+ +
2
x’
22.6 13 30.4
13.9 13 18.0
4.0 15 8.0
30.9 16 34.3
‘1 X -
;
;
-
3 X
-
I
2
4
+
x’
x’ X
; X
X X
10.5 19 23.4
19.0 12 16.2
14.1 16 19.8
7.7 12 8.2
l
* Indicates best one variable, whether retained in model or not. 1, 2, 3. 4, indicates position in four-variable model. + Indicates statistical significance and inclusion in model. - Indicates statistically not significant at 0.5 entry level. X Indicates variable not considered in model.
were not available for 1962. The results are shown. in a rather unconventional manner, in Table 1. More detailed information is not presented due to the complexity of the models, and to the preliminary purposes of this stage of the analysis. Population change is indeed important, except for black male CVD mortality 1968-72. The great importance of median age of the population for these agestandardized rates may lie in its reflection of past population change. There is a tendency for white mortality to be more associated with economic development and black with poor conditions, especially for the earlier period. The most important measures of change for whites is the percentage of farmers working 100 days or more off the farm, which is reflective of the rural population now commuting to factory jobs but not moving to cities. The pattern of relations between the sexes is rather confused. The most striking development is the emergence of similarly high degrees of explanation for white male and black ferntile, and the loss of explanation for black male CVD mortality. The results of the lagged regression are not shown for reasons of space. All of the model
explanations are much weaker using 1962 than 1972 socio-economic data for 1968-72 mortality. The most important variables are similar to those for the 1958-61 mortality associations. CANONICALANALYSIS Even the use of multiple regression techniques is reductionist when the need is to analyze multiple cause/multiple effect relations. Variables were deleted because of multicollinearity, for example, whereas it is probable that their effects are synergistic. The research problem is to examine the association of the entire ser of sock-economic conditions with the entire set of CVD mortality results and to compare the structure of relations over time. Canonical correlation analysis involves the creation of the linear combination of X set variables and the linear combination of Y set variables such that the resultant canonical variates are maximally correlated. More than one set of linear combinations may be highly correlated, yielding several cannonical variates (factors). The major assumptions are linearity of rela-
Cardiovascular
mortality in the southeastern
variables and sets of variables, and for purposes of statistical testing, normal distribution. The inter-relations of variables are not a problem, as they are incorporated into the derivation of standard weights which create the variates. Multicollinearity does become a problem in the interpretation of the variable coefficients, however, and has led to the use of correlations between the original variables and the canonical variate as the canonical “loadings” [ 121. Measures of “redundancy” indicate explained variance, and the squared loadings for each variate divided by the number of variables yields the proportion of the variance in the variable set accounted for by a variate.* The sets of sex and race specific mortality data for 1958-1961 and 1968-72 are the dependent variables, and the sets of so&-economic variabtes for 1962 and 1972 the independent. After analyzing the regression results, it was hypothesized that the mortality experience of white males and black females would load together on a factor of economic hope, that there would be a rural poverty factor, and that the races rather than the sexes would separate on factors representing different environmental conditions. It was expected that the overall explanation would improve over time, and that a lagged canonical correlation would be weaker. The results are shown in Table 2. Total explanation (redundancy) increases from 20.3% to 27.2%. This is largely due to the associations of white male mortality. CVD death rates for black females and white males do load together, but hardly on a factor of tions among
l The interpretation of canonical variates and the derivation of redundancy, variation extracted, canonical Ioadings, canonical coefficients, and canonical variates are explained in Briggs and Leonard [9], Levine [12] and Cooley and Lohnes [13].
United States
263
hope: the associations in 1972 are with population change and room density, poverty, poor housing. In 1962, they are related oppositely to measures of income and environment. Whites are similarly related in both 1952 and 1972 to measures of change, but black male CVD mortality is more independent from black female. Black rates load together most in relation to income and education. “Working off the farm” is important mainly (and inversely} for males in 1962. Education, income, urbanization (urban, migration, black population change), working off the farm-in short, the stresses of development-emerge as strongest variables in 1972. Poverty is clearly important, but no rural poverty factor is easily differentiated from urban poverty. As expected, the lagged canonical cqrrelation of 1968-72 mortality and 1962 socio-economic data is weak, with total redundancy a mere 14%.
SUMMARY
DlSCUSSION
The complex variable relations and set linkages revealed by the canonical correlation analysis suggest numerous enigmas. Description, explanation, and speculation could occupy many pages. It is interesting to reverse the perspective, however, and note that all the so&-economic variables in combination “explain” only 20-30*% of the CVD mortality variance by county. The proportion is slightly more for white males and black females, and considerably less for black males. The socio-economic variables become more important with time, as development and change intensify, and are most important for the subgroup of the population that has been most involved in so&-economic development. These results suggest that there may indeed be an underlying physical environmental factor being increasingly submerged by the gathering stresses of so&-economic change. This
LEGEND l 1.1to 2.0 greater than -1.1 to -2.0 greater
2.0
than -2.0
UP Canonical
Variate Voriote
Fig. 7.
Scores 1
Canonical variate scores for the mortality set, variate 1 of the 1972 canonical correlation.
Totai redundancy for 1968-72 CVD Mortality All canonical correlations highly significant.
0.4268 0.2019 74.02, 0.6885
Trace variance extracted Variant redundancy Proportion of total redundancy Canonical correlation coefficient
0.2239 0.0255 9.5:; 0.3879
-0.3248 0.7183 0.4923 0.1783
0.03 I7
-0.2253
0.023 0.100 0.089 0.057 0.054 0.074
-0.1130 -0.0455 - 0.0672 0.1060 -0.0188 -0.0138 0.2658 0.2101 0.0001 0.1317 - 0.0082
correlation
CVD
0.2239 0.0520 25.676 0.4820
-0.7363 -0.1030 0.4180 -0.4100
0.0438
-0.3788
0.0536 - o.ooo7
for 19.58-61
0.3953 0.1207 59.40/, 0.5525
0.3418 0.7216 0.6445 0.7268
0.0555
0.4491
0.1286 0.2401
0.6613 0.0102 - 0.0034 0.3214 -0.0120 -0.1569 -
- 0.0679 0.0910 -0.0525 0.0905 -0.0234 -0.1049
-0.6885 0.1466 - 0.0636 -0.1253 0.1844 -0.0162 0.0612 0.0304 -0.0442 -0.1004 - 0.0072 0.3192
- 0.0866 -
0.0066
(32
Canonical
-0.0117
0.0078
0,
results
total redundancy
33.7 13.0 18.2 35.1
7.3
1.4 6.3 5.6 3.6 3.4 4.7 3.6 3.5 3.1 3.2 2.5
5.7 7.9 8.0 15.3 0.6 2.3 5.5 2.4 3.1 1.0
lOORf/ZR:
redundancy
data = 0.2719;
0.367 0.141 0.198 0.382
0.116
0.056 0.049 0.051 0.039
0.058
0.091 0.126 0.127 0.244 0.010 0.036 0.087 0.038 0.050 0.016
Rf
Variable
2. Canonical
-0.1529 -0.1864 0. I347 -9.3223 0.2154 -0.1798 -0.1439 0.2695 -0.0625 -0.3578
CV,
given 1972 socio-economic
0.1869 0.0445 16.5% 0.4879
0.531 I 0.4428 -0.1017 -0.5092
0.7799 0.2743 0.5955 0.8179
0.5344
- 0.2999 0.1548
0.2972 0.6456 -0.5584 -0.4148 -0.4685 -0.1979 0.35oI 0.3709 -0.3247 -0.3197 -0.1835
- 0.0208 - 0.0379 0.1741 0.1752 0.0567 0.3687 0.2097 0.1955 0.2223 0.2310 0.2566
0.0670
0.5201 0.5274 0.439 1 0.2489 -0.1176 0.3697 0.5973 0.2022 0.1307 0.0568
-0.2251 -0.3445 0.4096 0.6172 - 0.0524 0.0067 0.0085 -0.2065 0.3115 -0.0275
CVZ
loadings
Trace variance extracted Mortality variables Black (nonwhite) females Black (nonwhite) males White females White males
Socio-economic variables “1 Change population O’ Migration “1 Urban q0 Change black population Median age “/;, Foreign born Median education y0 Labor in manufacturing ‘?/, Labor in retailing Y’, Labor in government ’ 0’ Labor in professional/ managerial Median family income “/;, Poverty income H; Old housing /0 Inadequate plumbing ‘?; Room density > 1.06 7; Budget/Health :d Change value added “/, Low farm income “/, Change farm land % Land in farms % Farmers working 100 days off farm
CV,
Canonical
1972 Variates
Table
Mortality
0.1799 0.0155 7.6”‘;) 0.2940
0.5344 0.3941 0.0486 -0.5257
0.1962
-0.3663
0.385 I 0.2636
- 0.4489 0.7331 - 0.7482 0.4437 0.5436 -0.5909
0.2868 0.3144 0.6119 0.4983 0.1585 0.1535
0.0159
0.0261
cv3
loadings
0.336 0.201 0.198 0.226
0.112
0.026 _.
0.120 0.052 0.054 0.027 0.068 .-
0.157 0.029 0.035 0.054 0.014 0.007
0.002
0.008 -
data = 0.2031.
35.0 20.9 20.6 23.5
13.4
3.0 3.1 _
.__
14.4 6.2 6.5 5.4 3.2 8.1
18.8 3.5 4.2 6.5
0.2
1.0 -
Variable redundancy Rf lOOR,2/ER’
given 1962 socio-economic
0.2010 0.0149 7.37,; 0.2127
0.2353 -0.5598 0.6388 0.1651
0.0652
0.2599
0.2857 0.1611
-..
- 0.0556 -0.2592 0.2493 0.1009 -0.1380 0.0595
- 0.2304 0.4009 0*1018 -0.5906 0.1098 0.2496
0.0888
0.3279 -
cv4
1962 Variates
E
Cardiovascular
mortality in the southeastern
United States
265
somewhat
counters the skepticism induced by the disparate spatial mortality pattern of the population subgroups. The pattern of canonical variate scores, however, invariably mirrors the mortality dichotomy between coastal plain and mountains. One example of this is presented in Fig. 7. It is thus the Enigma Area death rates that best are explained by the socio-economic analysis, and the intermediary, dynamic piedmont zone that is most problematic. Clearly, socio-economic factors must be included along with physical environmental factors in the frame for any research design. A typology based on canonical variate scores would be invaluable to classifying and selecting counties on a comparative basis for in-depth field study.
Georgia. U.S. Geol. Surv. Prof. Paper No. 574-C. U.S. Govt. Printing Office, Washington, D.C. 1970. 5. Sauer H. I. Descriptive associative methodology. In Geochemistry and the Environment, Vol. -III, p. 121. National Acad. Sci. Washington, D.C., 1978. 6. Camel J. The contribution of the social environment to host resistance. Am. J. Epidem. 104, 109, 1976. 7. Cassel J. The contribution of the social environment to host resistance. Am J. Epidem. 1Oq 109, 1976; Tassel J. and Tyroler H. A. Epidemiologic study of cultural change, health status and the recency of-industrialixation. Archs Enuir Hlth 3. 25. 1961: James S. A. and Kleinbaum D. G. Socioeconomic stress and hypertension related mortality rates in North CarolinaI‘Am. J. oubt. Hlth 66. 354. 1976: Neser W. B.. Tvroler H. A. * and Cassell J. C. Social disorganization and stroke mortality in the black population of North Carolina.
Acknowledgement-The cardiovascular mortality data used in this study were developed and refined by Herbert I. Sauer after years of experience and are invaluable to further study.
8. Briggs R. and Leonard W. A. IV. Mortality and ecolog&d structure: a canonical approach. Sot. Sci. Med. 11.757, 1977; Kotchen J. M. and Kotchen T. A. Geographic effect on racial blood pressure differences in adolescents. J. Chron. Dis. 31, 581, 1978; Robert R. E., McBee G. W. and MacDonald E. F. Social status, ethnic status and urban mortality: an ecological approach. Tex. Rep. Biol. Med. 28, i3, 1970; Wilt& D. M.. Walklev R. P.. Pinkerton T. C. and Yavback M. The Ho&9 Environment and Family Life: *A Longi-
Am. J. Epidem.
REFERENCES Jolliffe N. and Archer M. Statistical associations between international coronary heart disease death rates and certain environmental factors. J. Chron. Dis. 9,636, 1959; McGill H. C. Jr. Geographic Pathology of Artherosclerosis. Lea and Febiger, Philadelphia. 1958; Keys A. (Ed.) Coronary heart discasc in seven countries. Circulation 41, 1970, suppl. I; Kagan A. et al. Epidcmiologic studies of coronary heart disease and stroke in Japanese men living in Japan, Hawaii, and California: demographic, ph&ical, -dietary, and biochemical characteristics. J. Chron. Dis. 27. 345. 1974. Kotchen J. and Kotchen T. A. Geographic effect on racial blood pressure differences in adolescents. J. Chron Dis. 31, 581, 1978. Angino E. A. et al. Water: trace elements in solution. In Geochemistry and the Environment, Vol. 111, p. 32. National Acad. of Sciences, Washington, DC., 1978. Sauer H. I. Counties with extreme death rates and associated factors. Am. J. Epidem. 99,258, 1974; Sauer H. I., Payne G. H., Council C. R. and Terre11 J. C. Cardiovascular disease mortality patterns in Georgia and North Carolina. Pub/. HIth Rep. 81, 455, 1966; Schacklette H. T., Sauer H. I. and Miesch A. T. Geochemical environments and cardiovascular mortality rates in
tudinal Mental
93, 166, 1971.
Study o/the Effects of Housing on Morbidity Health. Johns Hopkins Press, Baltimore,
and
1962. 9. Briggs R. and Leonard W. A. IV. Mortality and ecolo&al structure: a canonical approach. Soi Sci. Med. 11, 757, 1977; Pyle G. F. Heart Disease, Cancer and Stroke in Chicago. University of Chicago, Department of Geography research paper no. 134,ChicaRo, 1961; Robinson V. B. Modeling spatial variations in heart disease mortality: impl&ions of the variable subset selection process. Sot. Sci. Med. 12D. 165, 1978. 10. Briggs and Leonard, op cit. 11. Kuller L. H. et al. Nationwide cerebrovascular disease mortality study III. Accuracy of the clinical diagnosis of cerebrovascular disease. Am. J. Epidem. 90, 556, 1969.
12. Levine M. S. Canonical Analysis and Factor Comparison. Sage University paper series on Quantitative Analysis in the Social Sciences, series no. 07-006. Sage Publications, Beverly Hills and London, 1977. Data 13. Cooley W. W. and Lohnes P. R. Multivariate Analysis. Wiley, New York, 1971.