The changing association between social status and coronary heart disease in a rural population

Soc, Sc~ & Med, Vol 14A, pp 191 to 201

0160-7979/80/0501-019150200/0

© Pergamon Press Ltd 1980 Printed m Great Bmtam

THE C H A N G I N G ASSOCIATION BETWEEN SOCIAL STATUS A N D C O R O N A R Y HEART DISEASE IN A RURAL P O P U L A T I O N HAL MORGENSTERN Department of Epidemlology and Public Health, Yale University School of Medicine, New Haven, CT 06510, U.S.A. Abstract--Until recently, inconsistent findings regarding the association between social status and cqronary heart disease (CHD) have been explained primarily in terms of methodologlc differences among studies. However, a closer examination of selected findings reveals that the assocmtlon may have changed from positive (increasing risk with higher social status) to negative (increasing risk with lower social status) in certain urban populations as the absolute rate of CHD was also changing, following a period of rapid socio-ecologic change or "modernization". The purpose of this study Is to Investigate a possible change in social status effect and to examine its biological basis for the white adult population of a rural county in Georgia between 1960 and 1974. While an apparent change in the association between social status and CHD was found for men in the predicted direction, no trend was found for women. The change was most dramatic among men under the age of 55 for whom the age-standardized ratio measure of association shifted from sigmficantly greater than one (the null value) to significantly less than one. This result was concluded to be vahd and is consistent with the finding of a substantial decline in CHD mortality during the same period for men in the study population but not for women. There is convincing evidence that the changing effect of social status was partially due to differential changes in certain biological risk factors of CHD, as intervening factors--particularly blood pressure increases among younger men during the 1960's. Alternatively, there was no support for the hypothesis that social status modified the effect of biological factors on CHD. Major sex differences in the findings and the lrnplications of these results are discussed in the general context of social epidemiologic research.

INTRODUCTION

The underlying conceptual hypothesis of this study is that C H D is a disease that characterizes the "modernization" of a society during and immediately after a period of rapid industrial growth and urbanization. The process of modernization is composed of many interdependent changes, including the intense application of scientific technology, the specialization of labor, the concentration of political power and economic decision making, and the replacement of ascription with achievement as a criterion for organizational movement [10]. In certain cultures the net result of these socio-ecologic changes appears to be the increased interdependence of people who do not know each other and who are in competition for limited resources. Consequently, modern social, political and economic institutions make a number of growing demands on the individuals who operate within them: for example, greater acceptance of occupational and geographic mobility, more awareness and tolerance of human diversity and new experiences, exposure to more information and conflicting opinions through the mass media, and less reliance on extended families for social support. It has been suggested that individuals, faced with these growing demands from the new social environment, gradually develop new values, attitudes, and behavior patterns which have been labelled collectively as "individual modernity" [10]. Because the development of the modern personality and life style within a given population is strongly influenced by such personal factors as amount of formal education and type of occupation [10], the extent of individual modernity should be closely related to social status* (or class). In fact,

The epidemiologic literature dealing with the possible relationship between social status and coronary heart disease (CHD) remains inconclusive despite fifty years of empirical investigations. Results have been dramatically inconsistent, suggesting associations that are positive (CHD risk increases with higher social status), negative (CHD risk decreases with higher social status), and various combinations between these two extremes [1-5]. Until recently, the predominant explanation for these inconsistencies has been methodologic differences, leading to the general conclusion that social status is not a valid "risk factor" of CHD [2,5,6]. However, a closer examination of selected findings reveals that the association between social status and C H D may have systematically changed from positive to negative in certain populations [4, 7-9]. The strongest evidence for this secular trend comes from the study of British mortality data in which the association appears to have changed substantially between 1930 and 1960 [4, 8, 9]. Less convincing support is also available for the urban population of the United States in which a similar change may have occurred after the mid-1930's [4].

* Social status refers to the set of attributes among adults who occupy common positions in a status or prestige hierarchy and who share a particular life style that mv01ves components of needs, values, attitudes, asplrati0ns, opportunities, habits, and expectations [11] Address reprint requests to Dr Morgenstern. 191

192

HAL MORGENSTERN

others have shown that higher status persons become engaged in the modern way of life before lower status persons [10]. Specifically, we would expect the upper classes to adopt more quickly a living pattern that increases the risk of CHD--possibly including: increased consumption of animal fat, more cigarette smoking, increased emotional stresses, and more sedentary jobs involving greater pressures [8]. It is claimed that the lower classes fail to make these early changes because they are least able to exert control effectively over their lifestyle and environment, not simply because they do not desire the change [12]. Consequently, lower status persons should eventually adopt the new life style and later suffer the resulting increased risk of CHD. Furthermore, as individuals and collectivities learn to adapt to their new social context and to adjust their life styles in accordance with desired health outcomes, the occurrence of the disease should eventually subside [13-18], first among the upper social classes and later among the lower classes. Thus, it is hypothesized that the association between social status and CHD should change from positive to negative during the period of modernization. The above theoretical framework implies a necessary connection between the putative changing effect of social status on CHD and the changing incidence of the disease in the population, though it is difficult to predict the precise relationship, There is little doubt that the rate of CHD increased in the United States between the 1920's and the 1960's [19-21]. In addition, there is empirical support for a general levelling off and decline in the cardiovascular mortality rate since the 1960's in both the United States [21-23] and Great Britain [24]. It is yet to be determined, however, whether the incidence rate of CHD has actually decreased in recent years [21] and

whether the change is related to social status. Nonetheless, many investigators currently attribute the observed mortality decline to systematic changes in routine behavioural patterns [e.g. 8, 18]. METHODS

A cohort of adults from the Evans County Heart Study [25], which was followed prospectively from 1960, has been selected to test the hypothesis of a changing social status effect because it is believed that the rural Evans County population experienced similar social changes in the 1950's and 1960's as did the urban U.S. population several years earlier [26]. Between the 1950 and 1960 censuses, the Evans County population grew in size after shrinking in previous decades, the composition of the population suddenly became more "urban", and the proportion of the labor force engaged in agricultural occupations decreased from 53 to 26% [27]. The study population for this investigation consists of all white adults, 40 years of age and older, who participated in the first Evans County examination in 1960. This group of 663 males and 687 females was reexamined in 1967 and followed for detection of deaths until 1974 [28, 29]. The original sample consisted of 92% of the white population in the community at least 40 years of age in 1960. Between 1960 and 1967, 4% of the sample was lost to follow-up (excluding deaths), and 83% of the original cohort was reexamined in 1967. Of those known to be alive in 1967, survival information, including cause of death recorded on the death certificate, is complete until the end of 1974. Table 1 summarizes the frequency of new and existing cases of CHD and deaths between 1960 and 1974. In order to make inferences about the hypothesized change in social status effect, analyses

Table 1. Number of subjects (N)*, prevalent (P), incident (I) cases of CHD, CHD deaths (De), and deaths from all other causes (Do), by sex, age in 1960, and time of observation: The Evans County Heart Study 1960

1960-67

Age (1960)

N

P

I

Dc Males

40-44 45-49 50-54 55-59 60-64 65-69 70+ Total

110 144 115 103 72 67 52 663

1 6 4 11 9 15 8 54

9 11 8 12 8 16 7 71

0 6 5 11 5 18 13 58

40-44 45-49 50-54 55-59 60-64 65-69 70+ Total

122 117 122 87 95 84 60 687

0 2 1 3 5 2 4 18

1967-74 Do

N

Dc

Do

5 7 3 9 8 13 15 60

105 131 107 83 59 36 24 545

0 8 3 4 8 4 3 30

6 13 9 10 15 14 15 82

Females 0 0 2 4 , 0 2 3 0 6 4 1 8 3 1 5 9 5 11 12 8 13 35 15 47

120 115 116 78 89 68 39 625

1 3 3 3 4 3 5 22

4 6 3 3 12 10 14 52

* In 1960, N represents all examined subjects; in 1967, N represents all subjects who were presumed alive.

Social status and coronary heart disease have been performed on three types of data: CHD prevalence (1960 and 1967); incidence (1960-67); and mortality (1960-67 and 1967-74). CHD was detected from medical histories, electrocardiograms (ECG) at both exams, and death certificates and included subjects who were judged as "definite or probable" cases of myocardial infarction, angina pectoris, sudden cardiac death, and "chronic heart disease" [29]. Social status is measured with the McGuire-White index which is a modified Warner scale adapted to rural populations [30]. A composite index ranging from 12 (highest status) to 84 (lowest status) is derived by weighting scores on three prestige scales: occupation, education, and source of income--based on the head ofgach household. For most of the analyses, this variable has been dichotomized at the median value for the entire study population in 1960. The search for- a biological explanation of social status effects included the following variables: age, serum cholesterol, systolic and diastolic blood pressure, Quetelet index (a measure of obesity formed by taking the ratio of weight to height squared times 100), smoking status, history of diabetes, any ECG abnormality (excluding diagnostic criteria for CHD), hematocrit, and pulse. These variables are considered in three analytic contexts accordirlg to the possible type of association with social status and CHD. First, age is controlled in the analysis as a potential confounder since it is a risk factor of CHD and since it is not influenced by social status. Secondly, all other factors (together with age) are treated in the analysis to explain any observed social status effect--i.e, as possible intervening links between certain life style factors and the occurrence of CHD. Two methods are used to investigate whether certain biological factors ---either singularly or in combination--reflect such intervening mechanisms: (1) the association between social status and CHD is tested, controlling for other biological predictors of the disease, including age as a potential confounder; and (2) the associations between social status in 1960 and subsequent changes m certain biological factors (1960-67) are tested, controlling for baseline values in 1960 and age. Thirdly~ social status is considered as a potential modifier of certain biological factors which increase the risk of CHD. This type of etiologic relationship would mean that the particular clinical pathology resulting from a given life style factor will depend on the pre-existing biological conditions which may be unrelated to the life style variables or social status. In order to assess such "effect modification" [31] between social status and biological risk factors-either singularly or in combination--tests for statistical interaction, assuming an additive model, are done in two ways: (1) with both predictor variables measured on interval scales, a conventional partial F-test is done for the product term (i.e. social status index × biological value or score) as an independent predictor of CHD; and (2) with both predictors dichotomized, the Z-test of Hogan et al. [32] is used. Testing associations is done by one of three related methods, depending on the type of data. Stratified analysis is used when the dependent variable is binary (e.g. CHD) and when there is only one control variable (i.e. age as a potential confounder). Statistical

193

significance is obtained from the Mantel-Haenszel test [33], and point estimation is done with standardized ratio measures of association (or "relative risk") [34]. For example, in the analysis of prevalence data, a comparison of "rates" for high versus low social strata results in an age-standardized prevalence ratio (SPR). With incidence and mortality data, the computed measures of association are the standardized risk ratio (SRR) and standardized mortality ratio (SMR), respectively. With a binary dependent variable and multiple control factors (including age), a method called "multivariate adjustment" is employed [-35, 36]. While this method is analogous to standardization, stratification of the control variables is not required. Observed cell frequencies of the crude 2 × 2 contingency table are compared with the values expected under the null hypothesis of no independent effect due to the study factor. An "adjusted" ratio measure of association-i.e. adjusted prevalence ratio (APR), ARR, or AMR--is derived to estimate the effect attributable to the study factor, independently of its association with the control variables. The probability of each subject becoming a case is estimated from a multiple logistic model that includes a function of the "biological" risk factors. These probabilities are summed within each category of the study factor to estimate the number of cases (and noncases) expected in each group under the null hypothesis, conditional on fixed marginal frequencies. In this study, the logistic probabilities are estimated from the linear discriminant coefficients as described by Cornfield [37]. The expected cell frequencies are then used to compute an expected measure of association which is an estimate of the crude study factor effect that would be expected under the null hypothesis. The adjusted ratio measure of association is computed by dividing the observed crude measure of effect by the expected measure, analogously to standardization [38]. A test of significance is done with the common Pearson chi square statistic, comparing observed and expected cell frequencies [35]. With a continuous dependent variable (e.g. change in blood pressure) and multiple control variables, an extension of the above method, called "'residual analysis" is used [35, 38]. The object of this method is to measure the association between the study factor and the residuals derived from a multiple regression model that includes a function of control variables as predictors of the dependent variable and excludes the study factor. For a binary study factor (e.g. social status), statistical significance of the study factor effect is obtained with a t-test of the difference in mean residuals. Derivation of an appropriate function of control variables in the two multivariate methods involves statistical as well as non-statistical considerations. A pool of possible predictor terms was created from the previous list of explanatory variables plus selected product and quadratic terms. Inclusion of specific terms was based on the combination of biomedical and social theory, previous empirical findings, and intuition. The actual function was generated by a complex "stepwise" procedure that first considers linear terms for entry into the model, followed by product and quadratic terms. New terms were added

194

HAL MORGENSTERN Table 2. Comparison of CHD mortality for the two follow-up periods (1960-67 and 1967-74), for ages 47-81 at the beginning of each period, by sex and social status in 1960 Social status

Crude CHD mortality "rate"

Comparison of "rates"

(1960)

1960q57

1967 74

SMR*

S%Rt

Low High Total

0.097 0.128 0.112

Males 0.64 0.046 0.055

0.64 0.27 0.45

36 73 55

Low High Total

0.027 0.030 0.029

Females 0.045 0.026 0.036

0.89 0.99 0.99

11 1 1

* The age-standardized mortahty ratio, comparing the second period to the first. Age is stratified into five 7-year strata. Correction is made for the difference in the mean follow-up periods (85.5 and 76.5 months). t The age-standardized proportional reduction from the first to the second follow-up period (in %o).

or subtracted from the model until little additional predictive or discriminatory power was obtained, Because of the moderate correlations a m o n g potential predictors, the model never grew to more than fi~e terms. Nevertheless, it should be emphasized that the addition of terms to the model does not change the results appreciably for any of the analyses presented in this paper. RESULTS Since the incidence of C H D was only detected for one 7-year period (1960-1967) without identification of the exact year of onset for each case, it is not possible to estimate any change in C H D incidence for a particular age group. However, a comparison of C H D mortality was made between the two periods, 1960-67 and 1967-74, correcting for different average

lengths of follow-up (85.5 and 76.5 months, respectively). Table 2 presents the results of this comparison for each sex, controlling for age at the beginning of each follow-up period. While the mortality rate for ' women remained nearly unchanged, the rate for men decreased by 55%, and the decline occurred in both social status groups. Since the hypothesized change in social status effect is contingent on a changing rate of disease occurrence, we might then expect the associations between social status and C H D to change for men and riot for women. Table 3 summarizes the estimates of the agestandardized measures of association between social status in 1960 and the various measures of CHD between 1960 and 1974. C o m p a r i n g either the two prevalence analyses or the two mortality analyses for men, the association appears to have changed from positive to negative, especially for men under the age

Table 3. The association between social status (high vs low) in 1960 and CHD: age-standardized ratio measures of association* by sex, age (in 1960 or 1967), and type of analysis Prevalence Age

1960

1967

< 55 >755 Total

6.28§ 1.57~ 1,92 ]J

Males 0.70 1.72§ 1.40

<55 ~>55 Total

0.53 0.71 0.69

Incidence

Mortality

1960-67

1960-67

1967-74

0.69 1.31 1.04

2.22 1.08 1.22

0.34§ 1.04 0.70

Females 0.70 0.53 0.84 0.75 0.82 0.72

t 0.71 0.71

1.28 0 0.67

* Each measure of association (SPR, SRR, or SMR) is standardized for age in 5-year categories, using the high social status group as the standard (i.e. the set of lweights). Significant associations are indicated as follows: ~(0.05 < P ~<0.10); §(0.01 < P ~< 0.05); II(P ~< 0.01) using a two-tail test. t Involves division by zero--Le, there were no CHD deaths among females under the age of 55 between 1960 and 1967

195

Social status and coronary heart disease

6.28 I"

i

,~

1.0 - - -

03 0,5

\\ \\ \\ \\ \\ \\ \\ \\ N\ \\ \\ \\

1.5? t //

.........

1.31

/ / / / I ~o~ l / /l'/~/---

,.%y. Y/./.

0.69

\\ \ \

\\ \\ N\ 02

N_\_. o

V~ /

M

P

/

M

Age <55 Age >, 5 5 ' Fxg. 1. Association between social status (high vs low) and CHD: age-standardized ratio measures of association (SMA)* for males, by age (in 1960 or 1967) and type of analysis--prevalence (P) 1960; incidence (I), 1960-67; and mortality (M), 1967-74. * Standardized prevalence ratio (SPR), standardized risk ratio (SRR), or standardized mortality ratio (SMR). Significant associations are indicated as follows: t(0.05 < P ~<0.10); ~(0.01 < P ~< 0.05) using a two-tail test. t

of 55 at the beginning of each period. In 1960, the high social status men under the age of 55 were significantly more likely to have C H D than were the low status men. By 1967 the relationship had reversed, though not achieving statistical significance. A similar trend is observed for C H D mortality among younger men for whom the association becomes significantly negative (SMR < 1) during the second period. In contrast to these results for men, the associations among women remain slightly negative, though statistically insignificant, for both follow-up periods. It should be noted that the magnitude of individual associations for the index of social status is always greater than and in the same direction as the associations for any of its cor0ponent scales: occupation, education, and source of income [40]. Furthermore, the associations are more or less consistent for all four manifestations of CHD: myocardial infarction, angina, sudden death, and chronic heart disease [40]. Thus there appears to be a changing association between social status and C H D for men but not for women in Evans County during the 1960's and the early 1970's. In order to illustrate the full extent of the observed trend among men, Fig. 1 combines results from three analyses: prevalence (1960); incidence (1960457); and mortality (1967-74). A dramatic shift from a significantly positive association to a significantly negative association occurs among younger men, and a minor change in the same direction occurs for older men during the same period. The implication from this data is that high social status men were relatively more likely to develop C H D before 1960 and low social status men were more likely to develop the disease after the mid-1960's. Further analysis reveals that the observed change in social status effect differs for farmers and nonfarmers (as classified in 1960) [40]. Among non-

farmers, the trend is similar to that observed for all men under the age of 55 (Fig. 1), with the association becoming progressively more negative over the study period. Among farmers, however, the association becomes most positive during the first follow-up period (SRR = 3.69, P = 0.01) and decreases after 1967 (SMR = 1.00). The findings suggest that the same hypothesized change in social status effect occurs among farmers several years after it occurs among non-farmers in the same general population. It thus appears that even farmers in a predominantly rural population eventually follow the pattern of C H D occurrence that characterizes a modernizing population [10]. Since it is possible that the apparent, change in social status effect among men is not specific to CHD [41, 42], a comparison of age-standardized mortality ratios has been made for all other causes of death, grouped together. The findings shown in Table 4 suggest that the observed change in association between social status and n o n - C H D mortality among men is not similar to the apparent change for CHD. In fact, there appears to be a moderate shift in the opposite direction: high status men are less likely to die of other diseases before 1967 but about equally likely to die of other causes after 1967 than are low status men. One could argue that the complementary nature of the observed trends for C H D and n o n - C H D mortality may be due to competing causes of death--i.e. lower status men were less likely to develop C H D before 1967 because they were dying of other causes first. However, this explanation is complicated by the findings for females in whom the association between social status and n o n - C H D mortality appears to have becomes:more negative. Despite statistically insignificant results for women, there is some suggestion that the apparent trend for C H D among men is paralleled for certain other fatal diseases among women. Perhaps, the health consequences of rapid social change are reflected in different disease for men and women. Table 4. The association between social status (high vs low) in 1960 and non-CHD mortality: agestandardized mortahty ratios,* by sex, age (at the beginning of follow-up), and follow-up period Age

1960-67

1967-74

< 55 >~55 Total

Males 0.29:~ 0.621 0.53~

0.95 0.94 0.94

<55 >~55 Total

Females 3.31t 1.37 1.59

0.73 0.35 0.54

* Mortality ratios are standardized for age in 5-year categories, using the high social status group as the standard (i.e. the set of weights). Slgnilicant associations are indicated as follows: "t"(0.05 < P ~<0.01); ~(0.01 < P 0.05)--using a two-tail test.

196

HAL MORGENSTERN

Table 5. Variables included in each of the three multivariate models used to predict CHD for males Predictor Variable

Time measured

~*

Prevalence analysis (1960) Age Serum cholesterol Any EEG abnormalityt History of diabetest

1960 1960 1960 1960

0.07311 0.011 IJ 1.781 fl 0.919

1960 1960 1960 1960 1960

0.607§ 0.685 ]r 0.014§ 0.0151l 0.0825

Mortality analysis (1967-74) Age 1960 Ever smoked x Quetelet Index 1960 Serum cholesterol 1967 Any ECG abnormality × hypertensiont 1967

0.096/I 0.296§ 0.009 2.149r[

Incidence analysis (1960-67) Ever smokedt Any ECG abnormalityt Age × systolic BP/100 Age x cholesterol/100 Hematocrit

* Estimates of the linear discrimmant coefficients. Significant values are indicated as follows: $(0.05 < P ~< 0.10); ~0.01 < P ~< 0.05): pI(P ~< 0.01}--using a two-tail test. t Indicates a binary variable. Hypertension is defined as either a systolic BP /> 160 mm or a diastolic BP >~ 95 mm. In order to determine whether the changing social status effect could be explained in terms of the measured biological risk factors of CHD, the association between social status and C H D was tested, controlling for the other biological predictors of the disease (including age), using multivariate adjustment. The control variables for each multivariate function are listed in Table 5. Theoretically, if the variables in the function were the only intervening factors linking social status and C H D , we would expect the crude measure of association to differ from one (the null value) and the adjusted measure to equal one. In practice, however, such results would not be expected because certain limitations in the study design lead to measurement and selection biases. It is unlikely that our observations will detect the relevant changes in both biological factors and disease status because social status and the biological predictors were measured cross-sectionally in 1960 [43]. The results

of the prevalence and incidence analyses show differences between the crude and adjusted estimates in the hypothesized direction (Table 6). However, repetitions of this procedure with age as the only control variable produce similar results [40], suggesting that most of the difference between the crude and adjusted measures of association is due to the effect of age, not to the gaediating effects of other biological variables of interest. Since it is possible that these findings resulted from the way in which the predictor variables were measured, a third analysis was performed. The association between social status in 1960 and CHD mortality between 1967 and 1974 was tested, controlling for changes in the multivariate risk score between 1960 and 1967. Again, the adjusted measure of association is closer to the null value (one) than is the crude measure. In this analysis, however, the difference cannot be due to an age effect because all subjects aged seven years between 1960 and 1967.

Table 6. Comparison of the crude and adjusted ratio measures of association* between social status (high vs low) in 1960 and CHD, for males, by type of analysis and age (in 1960 or 1967) Prevalence (1960)

Incidence ( 1960-67)

Mortality ( 1967-74)

Age

CRP

APR

CRR

ARR

CMR

AMR

<55 >/55 Total

4.86§ 1.925 2.48~

4.21:~ 1.77t 2.09§

0.79 1.53 1.23

0.74 1.44 1.11

0.44 0.68 0.66

0.51 0.83 0.77

* Adjusted measures of association were computed with "multivariate adjustment". The control varmbles were: the multivariate prevalence score for the prevalence analysis, the multivariate risk score for the incidence analysis, and the change in the multivariate risk score for the mortality analysis (see Table 5). Significant associations are indicated as follows: t(0.05 < P ~< 0.10); $(0.01 < P ~< 0.05): §(P ~ 0.01)--using a two-tail test.

197

Social status and coronary heart disease Table 7. Association between social status (high vs low) in 1960 and subsequent changes in selected CHD risk factors (196~67): statistically significant associations* (P ~< 0.10), by sex, age, and variable Age (1960) Variable (1960-67)

<55

/>55

Total

---IJ § -fJ

------

---§

--

-§

--:~ -----

:~ ----§ --

-----§ --

Males Reduce smoking Develop ECG abnormality Change in cholesterol Change in systolic BP Change in diastolic BP Change in Quetelet index Change in risk scorer Females Reduce smoking Develop ECG abnormality Change in cholesterol Change in systolic BP Change in diastolic BP Change in Quetelet index Change in risk scorer

* All significant associations are in the predicted directions--i.e, negative for all variables except smoking reduction - a n d are indicated as follows: :~(0.05 < P ~< 0.10): §(0.01 < P ~< 0.05); I](P ~< 0.0J}---using a two-tail test. Each test was done controlling for the baseline value of the variable in 1960 and age, using "residual analysis". t The multivariate risk score is a composite indicator of CHD risk using the variables listed in Table 5. The second method for identifying possible intervening factors is to test directly the association between social status in 1960 and subsquent changes in the biological variables (196ff457), controlling for baseline values in 1960 and age. Table 7 summarizes the results of these analyses for each of 6 C H D risk factors and for the multivariate risk score (RS), which is an estimate of C H D risk, based on observed values of the biological risk factors in 1960. While social status is not significantly related to changes in the multivariate risk score a m o n g women, there is a significant association for men which is confined to the younger age group. Specifically, the mean 7-year increase in the C H D risk score for higher status men

under the age of 55 was 0.027, while the mean increase for lower status men in the same age group was 0.046. T~ese findings are consistent with the apparent trend irl social status effect among younger men but not women. Furthermore, separate analyses for the individual risk factors strongly implicate blood pressure as the key intervening factor (Table 7). Thus, it is possible that the association between social status and C H D became more negative during the study period among younger men because of differential changes in blood pressure--i.e, lower social status men experienced greater blood pressure increases between 1960 and 1967 than did higher status men. For high and low status men under the age of 55, the mean in-

Table 8. Comparison of observed cumulative incidence (CI)* with the mean increase in the multivariate risk score (ARS)t between 1960 and 1967 for males, by social status in 1960 (1) Expected with aging effect

(2) Expected without aging effect

Social status (1960)

Observed CI*

ARSt

~oCI~

ARS~"

~oCI~

Low High Total

0.109 0.125 0.117

0.057 0.038 0.048

52 31 41

0.011 0.001 0.006

10 1 5

* (Crude) proportion of disease-free men in 1960 who subsequently developed CHD by 1967. t ARS is computed in two ways: (1) by letting each subject age 7 years between 1960 and 1967, thereby including the effect of age in ARS; and (2) by ignoring the aging of subjects, thereby excluding the effect of age in ARS. ~oCI = ARS/CI = estimated proportion of incident cases which is due to observed changes in the values of the biological risk factors included in the multivariate risk function (Table 5).

198

HAL MORGENSTERN

creases m systolic blood pressure were 3.6 and 8.4 mm Hg., respectively. In order to estimate the relative impact of the above results on the actual risk of CHD, the mean increase in the risk score (ARS) (as an estimate of the risk increase, based on changes in the measured risk factors) was compared with the observed cumulative incidence ("rate") of the disease for the same period (1960-67). The results presented in Table 8 suggest that as much as 41~o of the observed new cases among men was due to changes in the biological predictors listed in Table 5. Excluding the effect of age, the other predictors accounted for an estimated 5~o of all new male cases between 1960 and 1967. (Refer to footnotet of Table 8.) Moreover, results within social status groups are consistent with previous findings: while increases in the values of the biological factors, excluding age, accounted for 10~o of new cases among lower status men, such increases accounted for only one percent of new cases among higher status men. Concluding from the above results that differential changes in blood pressure and other measured biological predictors of CHD partially explain the observed changing association between social status and CHD assumes that those men whose risk score increased the most are the ones who eventually developed the disease. In fact, there is some evidence to support this assumption since the change in the risk score between 1960 and 1967 (ARS) is significantly associated with CHD mortality for men after 1967 (P = 0.02). The mean ARS for male CHD deaths between 1967 and 1974 was 0.057 while the mean ARS for men who survived until 1967 but who did not die of CHD during this period was 0.029. Although the association between blood pressure change and CHD mortality after 1967 is in the same direction, this latter association does not reach statistical significance (P > 0.10). Statistical tests for interaction effects between social status and each of the biological predictors, including the overall risk score, produced no significant results for any of the analyses within either sex [40]. Thus, there is no support for the hypothesis that life style factors, as reflected in social status differences, modify the effects of the commonly measured CHD risk factors. DISCUSSION

The observation of a declining rate of CHD mortality between the 1960's and the 1970's for men is consistent with observed trends for the total U.S. population during the same period [21, 23]. While the sex difference found in this study has not been observed for the U.S. population [21, 23], a similar difference was found in Great Britain [24]. As other investigators have noted, however, mortality trends may not reflect analogous changes in CHD incidence rates. For example, shifting medical care practices is one alternative explanation for the mortality decline [23] but receives little empirical support from the epidemiologic literature [21]. A more compelling explanation is that an epidemic of certain respiratory diseases during the first follow-up period may have caused the detection of excess CHD deaths [21, 44]. Unfortunately, there are not adequate data to test this

hypothesis in Evans County during the previous decade. Another possibility is that CHD deaths were more completely identified before 1967 because of the lack of a second follow-up examination in 1974, though the ascertainment of coronary deaths is regarded as sufficiently complete after 1967. It must also be recognized that the present analysis involves a "closed" cohort of subjects. Since new subjects were never added after the first exam in 1960, the study population became increasingly unrepresentative of the Evans County population as the follow-up progressed. Nevertheless, none of the above alternative explanations can explain why the decline in CHD mortality occurred for men but not for women. On the other hand, this sex difference is consistent with the primary finding of an apparent changing association between social status and CHD among men but not among women. The inference of a changing social status effect is largely dependent on combining results from three types of analyses which may be differentially biased. For example, the finding of a significant positive association between social status and CHD prevalence in 1960 may not reflect similar differences in incidence prior to 1960. One major source of "bias" in crosssectional studies is the "selective survival of cases" --i.e. when the study factor is associated with the survival rate of cases. If high social status cases lived longer than low status cases prior to 1960, low status cases would be underrepresented in the prevalence data, leading to a positively exaggerated measure of association. While we have no way of testing for this source of bias prior to 1960, it is possible to compare the case-fatality rates for high and low social status men after~ 1960. No significant association was found between social status in 1960 and the subsequent 7-year mortality among prevalent and incident cases for either sex [40]. In fact, for men under 55, the age-standardized case-fatality ratio for high versus low status groups was somewhat greater than one, suggesting that the corresponding estimate of the standardized prevalence ratio (SPR) was an underestimate of the actual measure. Since, selective survival of cases in the necessary direction was not observed after 1960, it is unlikely that it occurred prior to 1960. Therefore, it is very probable that the positive association found for men in the prevalence analysis was reflecting an analogous difference in incidence rates prior to 1960. Another problem with cross-sectional studies is that the actual direction of the observed association may be ambiguous--i.e, the occurrence of the disease might have preceded changes in the study factor, leading to a spurious prevalence finding. However, for this condition to have resulted in a positive association between social status and CHD prevalence, the development or onset of the disease would have had to be followed by upward social mobility prior to 1960~an unlikely possibility. While 44~o of the reexamined males increased their social status between 1960 and 1967 through occ~apational gains, incident cases were no more likely to increase their occupational status during the 7-year period than were noncases [40]. Thus, we may conclude that the social status effect observed among younger men was not due to selective social mobility following disease onset.

Social status and coronary heart disease Since the treatment of social status was limited to cross-sectional measurement in 1960 for all of the analyses presented in the previous section, it is possible that a change in social status--i.e, social mobility--may have accounted for the major findings of this study, rather than a changing social status effect. However, two additional analyses appear to negate this hypothesis. First, using social status in 1967 as a predictor of CHD prevalence in 1967 and CHD mortality after 1967 produces similar results as those presented in Table 3 for social status in 1960

E40]. Secondly, occupational mobility was not consistently related to CHD incidence. While men who were upwardly mobile between generations did experience a 50~o excess of CHD (P = 0.17), men who were upwardly mobile within their adult life (before 1960) did not experience any excess CHD [40]. Furthermore. the effect of upward intergenerational mobility occurred among the men who were low status in 1960 (SRR = 2.78, P = 0.02) but not among the high status group (SRR = 1.03, P = 0.99). Since thos+ men who achieved high social status by 1960 probably experienced more changes due to their social mobility, we may not conclude that upward mobility, per se, increased the risk of CHD among Evans County men. Perhaps, a more tenable explanation is that upward social movement from childhood to adulthood is only deleterious when accompanied by some degree of perceived failure to achieve one's goals, as reflected by 10wsocial status in 1960. In other words, it may not be the incongruity between early development and later life styles that predisposes one to CHD but rather the inability to achieve one's early expectations. Another explanation for the results presented in Fig. 1 is that the differences in point estimates of association are due to the aging of the study population rather than to a changing social status effect. If high social status men were more likely to develop CHD earlier in life, compared to low status men who tended to get the disease later (if they survived other hazards), the age-specific risk. ratios for high versus 10wstatus men could have remained unchanged over time in Evans County. Assuming this were true, we would expect low social status men 55 and older, to experience a relative excess of the disease, especially after 1967. Contrary to this prediction, it is high status men in this age group who continue to experience more disease; in fact, the association is actually more negative for men under 55 (SMR = 0.34) than for older men (SMR = 1.04) (Table 3). Thus, we may conclude that the observed trend in the relationship of social status to CHD among men is not simply due to age modification of a stable social status effect but to a changing age-specific association in Evans County between the 1950's and 1970's. The fact that this finding was predicted on the basis of previous observations of large heterogeneous, predominantly urban populations gives this interpretation of the present results added generalizability. The findings of this study suggests that socio-ecologic factors involved in the process of modernization affect the rate of CHD by differentially forcing segments of the population to change their life styles. Results based on multivariate analyses suggest that

199

systematic changes in certain biological risk factors, particularly blood pressure, act .as intervening links between life style factors and the development of CHD. This conclusion is consistent with the findings of two related British studies [45, 46] which explained both the rising cardiovascular disease rate for men before 1956 and the reversal of its association with occupational status in terms of blood pressure changes. These studies also reported no secular trendsfor women. It should be noted that the involvement of blood pressure as an intervening factor could have been easily missed using conventional multivariable analysis. (Refer to the prevalence and incidence results presented in Table 6.) Finally, in the absence of any significant interaction effects, we may conclude that social status does not appear to modify the effects of the major biological risk factors but to predict changes in certain biological factors that subsequently increase the risk of CHD. Because of the lack of longitudinal behavioural data in the Evans County Study, it is impossible to provide a behavioural explanation for the observed trend in the social status effect. Nevertheless, the sex differences make many explanations implausible. For example, it is not likely that substantial changes in dietary patterns would have occurred for men but not for women. Yet, since most female subjects remained unemployed during the study period, it is possible that certain job-related factors could explain a trend that was only observed among men. The credibility of this type of explanation is enhanced in view of the substantial shift from farm to non-farm occupations during the 1950's and 1960's. In 1960, 41~o of all , employed male subjects were farmers; and within 7 years, 30~o of these men had shifted to non-farming occupations. While there were approximately equal numbers of high and low status farmers in 1960, low status farmers were nearly 2½ times as likely to become non-farmers as were high status farmers (P = 0.01) [40]. In most cases, these occupational changes involved little or no social mobility (as measured with the McGuire-White Index). Nevertheless, other behavioural changes may have occurred, such as a decrease in the amount of on-the-job physical activity. While there is some evidence that jobrelated physical activity was related to CHD in Evans County [47], separation of the physical activity effect from other occupational effects is not possible with the available data [40]. Another possible explanation for the observed trends among males is that increasing job pressures accompanied the shift to nonfarming occupations. Previous studies have shown that occupational "stress" is often associated with the development of both CHD and hypertension [48-50]. Although the differences in results for men and women are consistent for the various analyses, they lend some doubt to the singular importance of CHD as a reflection of the impact of modernization. While no trend was observed for the effect of social status on CHD among women, there was empirical evidence for a trend in the rate of other fatal diseases that paralleled the trend for CHD among men (Table 4). These findings suggest either that the life styles of women were not changing in some way as were those of men or the the health consequences of these life style factors were different for the two groups.

200

HAL MORGENSTERN

The implication of this study ~s that the associations between life style factors and certain diseases may systematically change during the secular course of these diseases within given populations. Such trends can seriously complicate the investigations of the etiologic importance of psychosocial and behavioral factors. While this makes causal inference more difficult for a particular study, knowledge of major trends can enhance our understanding of disease etiology. Acknowledgements--This study evolved from my dissertation in the Department of Epidemiology at the University of North Carolina (Chapel Hill) where Dr John Cassel served as my advisor from 1974 to 1976. Dr Cassel was directly responsible for many of the ideas in this study and helped to shape its final form. I would like to thank the members of my doctoral committee who reviewed the dissertation: Drs Michael Ibrahim, H. A. Tyroler, Allan Smith, Berton Kaplan, Sherman James, and James House. I would like to thank Dr Lisa Berkman of Yale University, who contributed several helpful suggestions to the final draft, and Dr Curtis Hames of Claxton, Georgia, who permitted me to use the Evans County data for my research. This study was supported by two training grants from the National Institutes of Health (No. 5-T32-HL07055-01 and No. 2-A03-AH00534-03) and by three research grants from the Public Health Service (No. HE-00341), the National Cancer Institute (No. 1-P01-CA-16359-05), and the Henry J. Kaiser Family Foundation. REFERENCES

1. Logan W. P. D. Social class variations in mortality. Br. J. prey. soc. Med. 8, 128, 1954. ! 2. Lehman E. W. Social class and coronary heart disease.~ a sociological assessment of the medical literature. J.' chron. Dis. 20, 381, 1967. 3. Marks R. U. Factors involving social and demographic characteristics: a review of empirical findings. Milbank mere. Fund q. bull. 45, 51, 1967. 4. Antonovsky A. Social class and the major cardiovascular diseases. J. chron. Dis. 21, 65, 1968. 5. Jenkins C. D. Psychologic and social precursors of coronary disease (Part I). N. EngL J. Med. 284, 244, 1971. 6. Jenkins C. D. Psychologic and social precursors of coronary disease (Part II). N. EngL J. Med. 284, 307, 1971. 7. Jenkins C. D. Recent evidence supporting psychologic and social risk factors for coronary disease (Part I). N. Engl. J. Med. 294, 987, 1976. 8. Cassel J., Heyden S. and Bartel A. G. Incidence of coronary heart disease by ethnic group, social class and sex. Archs intern. Med. 128, 901, 1971. 9. Halliday M. L. and Anderson T. W. The sex differential in ischaemic heart disease: trends by social class 1931 to 1971. Epidem. Commun. filth 33, 74, 1979. 10. Inkeles A. and Smith D. H. Becoming Modern:Individual Change in Six Developing Countries. Harvard Univ. Press, Cambridge, MA, 1974. 11. Hunter S. M., Frerichs R. R. and Webber L. S. Social status and cardiovascular disease risk factor variables in children: the Bogalusa Heart Study. J. chron. Dis. 32, 441, 1979. 12. Conference on Future Directions in Health Care:A New Public Policy. Sponsored by the Institute of Medicine, The Rockefeller Foundation, Health Policy Program of the University of California at San Francisco, and The Blue Cross Association. New York, NY, February 15-16, 1977.

13. Dubos R Man Adapting, Chap. 10. Yale Univ. Pre:~s, New Haven, CT, 1965. t4. Mechanic D. Social structure and personal adaptation: some neglected dimensions. In Coping and Adaptation (Edited by Coelho G. V. et al.), Chap. 3. Basic Books, New York, 1974. 15. Tyroler H. A. and Cassel J. Health consequences of culture change--II. The effect of urbanization on coronary heart mortality in rural residents. J. chron. Dis. 17, 16% 1964. 16. Medalie J. H., Kahn H. A. and Neufeld H. N. Myocardial infarction over a five-year period--I. Prevalence, incidence and mortality experience. J. chron. Dis. 26, 63, 1973. 17. Omran A. R. A century of epidemiologic transition in the United States. Prey. Med. 6, 30, 1977. 18. Walker W. L Changing United States life-style and declining vlascular mortality: cause or coincidence? (editorial). N. Enol. J. Med. 297, 163, 1977. 19. Stamler J. The epidemiology of atherosclerotic coronary heart disease; Part I. Postgrad. Meal. 25, 610, 1959. 20. Anderson T. W. Mortality from ischemic heart disease: changes in middle-aged men since 1900. J. Am. reed. Ass. 224, 336, 1973. 21. Gordon T. and Thorn T. The recent decrease in CHD mortality. Prey. Med. 4, 115, 1975. 22. Walker W. J. Coronary mortality: what is going on? J. Am. reed. Ass. 227, 1045, 1974. 23. Cooper R., Stamler J., Dyer A. and Garside D. The decline in mortality from coronary heart disease, U.S.A., 1968-1975. J. chron. Dis. 31, 709, 1978. 24. Florey C. du V., Melia R. J. W. and Darby S. C. Changing mortality from ischaemic heart disease in Great Britain 1968-76. Br. Med. J. 1, 635, 1978. 25. McDonough J. R., Haines C. G., Stulb S. C. and Garrison G. E. Cardiovascular disease field study in Evans County, Ga. Publ. Hlth Rep. 78, 1051, 1963. 26. Cassel J. C. Review of 1960 through 1962 cardiovascular disease prevalence study. Archs. intern. Med. 128, 890, 1971. 27. United States Bureau of the Census. U.S. Census of Population. 1960, Vol. 1, Characteristics of the Population, Parts 1 and 12. U.S. Government Printing Office, Washington, D.C., 1963. 28. McDonough J. R., Hames C. G., Stulb S. C. and Garrison G. E. Coronary heart disease among Negroes and Whites in Evans County, Georgia. J. chron. Dis. 8, 443, 1965. 29. Cornoni J. C., Waller L. E., Cassel J. C., Tyroler H. A. and Hames C. G. The incidence study--study design and methods. Archs intern. Med. 128, 896, 1971. 30. McGuire C. and White G. D. The measurement of social status (unpublished research paper in human development, No. 3, revised). Department of Educational Psychology, University of Texas, 1955. 31. Rothman K. J. Synergy and antagonism in cause-effect relationships. Am. J. Epidem. 99, 385, 1974. 32. Hogan M. D., Kupper L. L., Most B. M. and Haseman J. K. Alternatives to Rothman's approach for assessing synergy (or antagonism) in cohort studies. Am. J. Epidem. 108, 60, 1978. 33. Mantel N. and Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. J. Nat. Cancer Inst. 22, 719, 1959. 34. Miettinen O. S. Standardization of risk ratios. Am. J. Epidem, 96, 383, 1972. 35. Morgenstern H. and Smith A. H. Estimation of effect with multivariate adjustment (abstract). Am. J. Epidera. 110, 372, 1979. 36. Heinonen O. P., Slone D. and Shapiro S. Birth Defects and Drugs in Pregnancy, pp. 16-29. Publishing Sciences Group, Littleton, MA, 1977.

Social status and coronary heart disease 37. Cornfield J. Joint dependence of risk of coronary heart disease on serum cholesterol and systolic blood pressure: a discriminate function analysis. Fedn. Proc. Fedn Am. Socs exp. Biol. (suppl. II) 21, 58, 1962. 38. Miettinen O. S. Components of the crude risk ratio. Am. J. Epidem. 96, 168, 1972. 39. Tukey J. W. Methodology, and the statistlcian's responsibility for both accuracy and relevance. Star. Rep. 76, 253, 1976. 40. Morgenstern H. The changing association between social status and coronary heart disease in rural population (doctoral dissertation). University of North Carolina, Chapel Hill, NC, 1978. 41. Cassel J. The contribution of the social environment to host reslstence. Am. J. Epidem. 104, 107, 1976. 42. Syme S. L. and Berkman L. F. Social class, susceptibility and sickness. Am. d. Eptdem. 104, 1, 1976. 43. Halperin M., Wu M. and Gordon T. Genesis and interpretation of differences in distribution of baseline characteristics between cases and non-cases in cohort studies. J. chron. Dis. 32, 483, 1979. 44. Bainton D,, Jones G. R. and Hole D. Influenza and ischaemic heart disease--a possible trigger for

45. 46. 47. 48. 49.

50.

201

acute myocardial infarcation? Int. J. Eptdem. 7, 23l, 1978. Miall W. E. and Oldham P. D. Factors influencing arterial blood pressure in the general population. Clin. Sci. 17, 409, 1958. Miall W. E. Follow-up study of arterial pressure in the population of a Welsh mining valley. Br. med. J. 2, 1204, 1959. Cassel J., Heyden S. and Bartel A. G. Occupation and physical activity and coronary heart disease. Archs intern. Med. 128, 920, 1971. House J. S. Occupational stress and coronary heart disease: a review and theoretical integration. J. Hlth. soc. Behav. 15, 12, 1974. Herd J. A. Behavioural factors in the physiological mechanisms of cardiovascular disease. Presented at the First Annual Meeting of the Academy of Behavioural Medicine Research, Snowbird, Utah, 1979. Scotch N. A. and Geiger H. J. The epidemlology of essential hypertension: a review with special attention to psychologi9 and sociocultural factors--II. Psychologic and soc/iocultural factors in etiology. J. chron. Dis. 16, 1183, 1963.