Long-term Outcome of Myocardial Infarction in Women and Men: A Population Perspective

Viola Vaccarino1, Lisa F. Berkman2 and Harlan M. Krumholz1,3,4

1 Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT.
2 Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA.
3 Department of Internal Medicine Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT.
4 Center for Outcomes Research and Evaluation (CORE), Yale-New Haven Hospital, New Haven, CT.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Because of women's survival advantage, the impact of myocardial infarction (MI) on long-term mortality in women compared with men may be underestimated. The authors examined this issue in a community sample of 2,462 persons aged >=65 years living in New Haven, Connecticut, who were free of MI at baseline and were followed for 10 years (1982–1992). By using proportional hazards models with MI hospitalizations and the sex-MI interaction as time-dependent covariables, survival for the MI cases from the date of MI was compared with survival of persons who, at the same follow-up time, were still alive and free of MI. Women survived longer than men mainly in the absence of MI. The multivariable-adjusted hazard ratios of death were 0.53 in the absence and 0.87 in the presence of MI, and MI was associated with a greater risk of death in women (adjusted hazard ratio = 5.9) than in men (adjusted hazard ratio = 3.6) (p = 0.01 for the sex-MI interaction). When out-of-hospital fatal infarctions were considered, the impact of MI on survival in women compared with men increased. In conclusion, in this elderly cohort, when viewed from a population perspective, MI had a greater impact on mortality in women and significantly narrowed women's typical survival advantage over men. Am J Epidemiol 2000;152:965–73.

coronary disease; mortality; myocardial infarction; population surveillance; sex factors; women

Abbreviations: CHD, coronary heart disease; CI, confidence interval; EPESE, Established Populations for Epidemiologic Studies of the Elderly; HR, hazard ratio; MI, myocardial infarction.


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Several studies have compared long-term survival after myocardial infarction (MI) between men and women (1GoGoGoGoGoGoGoGoGoGoGoGoGo–14Go). The traditional approach has been to compare mortality between male and female MI patients, adjusting for age and other baseline differences. While these comparisons have yielded important insights, they have usually failed to take into account a population perspective.

The life expectancy of women and men differs (15Go). Because of their underlying survival advantage, female patients may appear to have a similar or even better long-term outcome after MI than men do, even if the disease has a greater impact on women's survival than on men's. Consequently, failure to account for gender differences in the absence of MI may lead to underestimation of the burden of MI on women's mortality.

The notion of considering expected survival when mortality rates for specific conditions are compared across different segments of the population is common in other fields of epidemiology, such as cancer epidemiology. Cancer mortality rates according to sex, race, and age are commonly expressed in terms of "relative survival rate," which is the ratio of the observed survival rate after cancer diagnosis to the expected survival rate based on population mortality rates for that specific group (16Go). This procedure allows adjustment for survival differences not related to the cancer across different population groups.

Procedures that take into account the expected population survival when mortality rates are compared across different groups have not been commonly used in cardiovascular epidemiology. The New Haven, Connecticut, cohort of the Established Populations for Epidemiologic Studies of the Elderly (EPESE) offered a unique opportunity to apply this methodology to the study of sex differences in long-term mortality after MI. In this elderly community sample, MI hospitalizations were validated and deaths were monitored throughout a 10-year follow-up period.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Study population
The New Haven cohort of EPESE is one of four sites funded by the National Institute on Aging (17Go). The sampling design of this cohort has been described in detail elsewhere (17Go, 18Go). Briefly, the cohort was assembled in 1982 by obtaining a probability sample of the noninstitutionalized New Haven population aged 65 years or older stratified according to three housing strata: public housing for the elderly (age and income restricted), private housing for the elderly (age restricted), and general community housing. The response rate for the combined strata was 82 percent, yielding a baseline sample of 2,812 subjects, including 1,169 men and 1,643 women.

Baseline data collection
Baseline data were collected during in-home, face-to-face interviews in 1982 by trained EPESE interviewers, who obtained information on each participant's demographic factors, medical history, and functional status. Chronic conditions were identified from participants' statements about whether a physician had ever told them that they had had an MI, stroke, diabetes mellitus, hypertension, or cancer. Patients reporting during the baseline interview that they had a previous MI (n = 324) were excluded from this analysis. Self-report of diabetes has been validated by medical record review and been found to be highly accurate (19Go). Our analysis also considered history of exertional chest pain, which was assessed by means of a subset of the questions from the London School of Hygiene Chest Pain questionnaire (20Go). We used exertional chest pain rather than Rose angina because a previous analysis of the EPESE data showed that exertional chest pain was a slightly better predictor of coronary heart disease (CHD) mortality than the total Rose scale was (21Go). Heart failure was considered present if the person was using digitalis and loop diuretic medications at the time of the baseline interview, as assessed by direct inspection of all containers for all prescription and nonprescription medications taken over the past 2 weeks.

CHD risk factors considered in the analysis included history of smoking, history of hypertension, blood pressure level, and body mass index. Subjects were classified as current, past, or never smokers on the basis of their self-reported smoking status. The Hypertension Detection and Follow-up Program protocol was used to obtain three seated blood pressure readings (22Go). After the systolic and diastolic blood pressures from the second and third readings were averaged, subjects were classified as follows: 1) systolic pressure <140 mmHg and diastolic pressure <90 mmHg, 2) systolic pressure 140–159 mmHg or diastolic pressure 90–94 mmHg, 3) systolic pressure 160–200 mmHg or dia-stolic pressure 95–99 mmHg, and 4) systolic pressure >=200 mmHg or diastolic pressure >=100 mmHg. Groups 3 and 4 were subsequently combined because there were few subjects in the highest blood pressure category.

Self-reported height and weight were used to calculate body mass index (kg/m2). These responses have been found to be highly accurate (19Go). Body mass index was classified as low (<23 kg/m2), intermediate (23–27 kg/m2), or high (>27 kg/m2) according to tertiles of the body mass index distribution.

Because the presence of basic activities of daily living limitations prior to an MI has been shown to be related to MI severity and mortality (23Go), we also considered functional status in activities of daily living. Participants were asked about their ability to perform six basic activities: eating, walking across a room, bathing, dressing, transferring from bed to chair, and using the toilet.

Assessment of MI
New cases of MI during follow-up (from inception of the cohort in 1982 to December 31, 1991) were identified through surveillance of hospitalizations in the two local hospitals in New Haven. Additional information on hospital admissions was obtained from Medicare Part A Beneficiary Bill History data from the Health Care Financing Administration. Matching data on hospitalization from these two sources indicated that our surveillance identified 95 percent of all CHD-related admissions, therefore assuring a fairly complete assessment of hospitalizations for MI in the study population.

New Haven is the only EPESE site that has undertaken a complete review of medical charts of all subjects hospitalized for suspected MI. All EPESE participants who were admitted to the two New Haven local hospitals during follow-up and had a recorded discharge diagnosis of acute MI (International Classification of Diseases, Ninth Revision, Clinical Modification codes 410.0–410.9) were identified and their medical records were reviewed to verify the MI diagnosis, as described previously (2Go). Briefly, subjects were considered to have had an MI if they fulfilled at least two of the following criteria: 1) central anterior chest pain lasting at least 15 minutes or other symptoms consistent with MI (acute pulmonary edema, cardiogenic shock, or cardiac arrest), 2) characteristic electrocardiographic modifications, and 3) typical rise and fall of serum creatine kinase with an increase of the MB fraction to 4 percent or more. If Q waves did not develop, serum enzyme elevations were required for diagnosis.

Subjects who experienced more than one MI during the study period were analyzed only in relation to their first event. However, when the first event did not meet the diagnostic criteria, subsequent hospitalizations for MI were identified and were reviewed. To capture MIs potentially misclassified as unstable angina, all first admissions with a discharge diagnosis of unstable angina during the same study period not preceded by an admission for MI were also reviewed to verify the potential occurrence of MI (2Go). Only three additional MI cases were found among the unstable angina admissions. In addition, to consider MI cases who failed to reach the hospital to be accounted for according to our MI definition, in some analyses we combined hospitalized MI and out-of-hospital CHD deaths (defined as described below).

Mortality endpoints
The main study endpoint was all-cause mortality to assure comparability of results with previous literature of sex differences in mortality after MI. We also think that total mortality was a better endpoint for this study, given the inaccuracy of the underlying cause-of-death classification in death certificates (24Go), especially among the elderly (25GoGo–27Go). However, sex differences in CHD and non-CHD mortality were also examined. Since our analysis dealt with hospitalized MI events, we examined out-of-hospital deaths of men and women, both for all causes and CHD, to rule out a potential bias due to sex differences in out-of-hospital fatal MIs.

Mortality during the 10-year follow-up period was ascertained by monitoring obituary notices in local newspapers, gathering information from relatives during follow-up, and by eventually obtaining the death certificates of all deceased subjects. Vital status at 10 years was known for all participants. A single nosologist coded all death certificates. CHD mortality was defined as an underlying cause of death coded 410–414 on the death certificate according to the International Classification of Diseases, Ninth Revision, Clinical Modification. Death certificates also provided information on site of death. Out-of-hospital deaths were defined as deaths occurring outside an acute-care hospital and therefore included deaths occurring in nursing homes or other chronic care facilities. This definition was used since the main purpose in examining these deaths was to assess fatal MIs missed by our surveillance of MI admissions in acute-care hospitals. Information on site of death was missing for 19 persons.

Statistical analysis
The purpose of the statistical analysis was to test whether the hazards of mortality differed between the men and the women who developed an MI relative to the hazards of mortality for the rest of the population. In other words, we wanted to test whether the association of sex with mortality differed in the MI group as compared with the rest of the population.

First, we performed bivariate comparisons of baseline characteristics between men and women according to whether an MI occurred during follow-up. Except for age, which was analyzed as a continuous variable, comparisons were presented as women-to-men prevalence risk ratios for each characteristic. Since there were many more observations for the group without infarction, inspection of the risk ratios provided a better idea of differences in the distribution of factors between women and men across the two groups (with and without MI) than did inspection of chi-square or p values. For two variables for which >=5 percent of the data were missing, body mass index (239 missing) and blood pressure group (120 missing), we included "missing" as an additional category.

Next, we constructed Cox proportional hazards regression models to assess sex differences in the incidence of MI and total mortality in the entire cohort. The proportionality assumption of the Cox model, checked by plotting the logarithm of the cumulative hazards for males and females, was satisfied. Survival curves for total mortality and incident MI according to sex were also calculated by using life table methods (28Go).

We then constructed a series of Cox proportional hazards regression models with time-dependent covariables to assess whether the association of sex with total mortality differed in the MI group as compared with the rest of the population. In these models, we tested whether there was a significant interaction between sex and MI on mortality. Because MI could have occurred any time during follow-up, both MI and the interaction of sex with MI were treated as time-dependent covariables and were updated continuously during the entire follow-up period on the date of the MI admission. This statistical methodology allows covariables to be updated prospectively over time (29Go). If a person developed an MI during follow-up, he or she entered the MI group on the date of MI admission; before that date, he or she contributed data to the population control group. Survival of the MI cases was calculated starting from the date of MI admission and, in each distinct time interval of the follow-up, was compared with survival of those who, at the beginning of the interval, were still alive and free of MI. Although risk factors, comorbidity, and functional status were reassessed a number of times during follow-up of this cohort, we chose to use only baseline information on these factors, since changes over time might be a consequence of MI.

To determine the impact of MI cases who failed to reach the hospital, the final model was repeated after we included out-of-hospital CHD deaths in the MI definition. Initially, out-of-hospital CHD deaths were included in this analysis by considering them to be MI cases with "instant" mortality, that is, with a survival after MI of 0 days. Because of model convergence problems, however, survival after MI for these cases ultimately was set to 0.5 days.

Because we knew of no available software to compute weighted proportional hazards with time-dependent covariables, instead we added dummy variables for type of housing to account for the stratified sampling design. The coefficients from the proportional hazards models were converted into hazard ratios, and 95 percent confidence intervals were calculated. The coefficient from the sex-MI interaction enabled calculation of the hazard ratio of death of women versus men in the MI and no-MI groups separately.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Study sample and bivariate analyses
Of the 2,812 persons who participated in the 1982 baseline interview, 324 reported a previous MI and were excluded from the main analysis. We also excluded 26 additional participants whose MIs could not be validated because of lost medical records or hospitalizations outside our surveillance area. The total sample for our analysis, therefore, was 2,462 persons.

During the 10-year follow-up, there were 182 incident MIs (86 in men and 96 in women) and 1,183 deaths (555 in men and 628 in women). The yearly incidence of MI remained constant during follow-up, at the approximate rate of 1 percent per year. The total number of person-years of observation was 17,832. Among subjects who developed an MI during follow-up, there were 387 person-years of observation after the MI. In the cohort as a whole, women had a lower incidence rate of MI (women-to-men hazard ratio (HR) = 0.62, 95 percent confidence interval (CI): 0.46, 0.83) and a lower mortality rate (HR = 0.64, 95 percent CI: 0.57, 0.72) compared with men (figure 1). The numbers of deaths, according to whether an MI occurred and according to sex, were as follows: in the absence of MI, 566 in women (40.7 percent) and 498 in men (56.0 percent); in the presence of MI, 62 in women (64.6 percent) and 57 in men (66.3 percent).



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FIGURE 1. Cumulative incidence of myocardial infarction (MI) and survival curves for men and women participants in the New Haven, Connecticut, Established Populations for Epidemiologic Studies of the Elderly, 1982–1992.

 
Among both the MI cases and the population controls, women were slightly older: the mean age was 74.1 years for men versus 74.9 years for women in the group that never experienced an MI during follow-up and 73.1 years for men versus 74.5 years for women in the group that developed an MI during follow-up. Compared with men, women were less likely to have >=12 years of education and to be married, had more preexisting medical conditions (history of hypertension, exertional chest pain, heart failure, and cancer), were more limited regarding activities of daily living, and more often had a body mass index outside the intermediate ("normal") range. Many of these differences were more pronounced in the MI group. In the latter, women also showed higher prevalence rates of diabetes and previous stroke. On the other hand, in both groups, men were more likely to be past or current smokers. There was little difference between the sexes in measured blood pressure level.

Sex differences in mortality by occurrence of MI hospitalization
By using a series of Cox proportional hazards models, we tested whether the interaction between sex and MI was significant before and after adjustment for the demographic and comorbidity factors assessed at baseline and listed in table 1. As shown in table 2, the interaction between sex and MI was statistically significant in all of the models. This interaction indicates that the survival advantage of women was modified by the occurrence of MI or, conversely, that the effect of MI on mortality was greater for women than for men. In fact, at each follow-up time, women had a lower mortality rate than men did, but only for those without a previous MI; for those who had experienced an MI, mortality was similar in women and men. Before adjustment for baseline characteristics, among those without a previous MI, women had a 40 percent lower hazard of death compared with men, while women had the same hazard as men (HR = 1.04) if an MI had occurred (excess risk due to MI for women relative to men, 74 percent; p = 0.004).


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TABLE 1. Comparison of demographic factors and comorbid conditions at baseline, and total mortality at follow-up, between women and men, according to whether a myocardial infarction (MI) occurred during follow-up, New Haven Established Populations for Epidemiologic Studies of the Elderly, New Haven, Connecticut, 1982–1992*

 

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TABLE 2. Female-to-male relative risks for 10-year all-cause mortality, according to whether a myocardial infarction (MI) occurred during follow-up, New Haven Established Populations for Epidemiologic Studies of the Elderly, New Haven, Connecticut, 1982–1992*

 
Because of the more unfavorable distribution of demographic factors and comorbidity in women, adjustment for these features tended to increase the female advantage in both groups. Age and other demographic factors had the strongest impact on the hazard ratio estimates, while adjustment for comorbidity other than CHD risk factors had the least effect. In the fully adjusted model, the hazard ratio of death for women compared with men was 0.53 (95 percent CI: 0.46, 0.61) in the absence of a prior MI and 0.87 (95 percent CI: 0.60, 1.26) in the presence of an MI. Therefore, while after control for potential confounders women had an almost 50 percent survival advantage over men in the absence of a prior MI, the female survival advantage was only 13 percent (and not statistically significant) in the presence of an MI (excess mortality risk due to MI in women relative to men, 64 percent; p = 0.01).

Impact of MI hospitalization on mortality
By considering the coefficients for MI and its interaction with sex in the last (fully adjusted) model shown in table 2, we expressed the results in terms of the effect of MI on mortality separately for women and men. MI was a stronger risk factor for mortality in women (HR = 5.9, 95 percent CI: 4.5, 7.8) than in men (HR = 3.6, 95 percent CI: 2.7, 4.8). The fact that the confidence intervals for men and women overlapped does not contradict the finding that women had a significantly higher risk of death due to MI than men did. The 95 percent probability of the confidence intervals was computed for the hazard ratios for each sex separately, while an appropriate test for equality of the two hazard ratios would have had to consider the two hazard ratios simultaneously. Therefore, while these confidence intervals are analogous to tests of statistical significance for the effect of MI within sex, they should not be used to test whether the effect of MI differs in men and women (30Go).

Contribution of out-of-hospital CHD deaths
When the overall out-of-hospital deaths were compared between men and women, no sex differences were found for out-of-hospital all-cause mortality (19.5 percent in women vs. 20.3 percent in men, p = 0.64), but out-of-hospital CHD mortality tended to be higher in women than in men (5.0 vs. 3.7 percent, p = 0.13). Similar results were obtained for the group never admitted for an MI. In the fully adjusted model, when out-of-hospital CHD deaths were included in the analysis as MI cases, the hazard ratio of death for women compared with men was 0.49 (95 percent CI: 0.42, 0.57) in the absence of a prior MI and 1.23 (95 percent CI: 0.92, 1.65) in the presence of an MI, corresponding to an excess risk of death due to MI in women relative to men of 151 percent (95 percent CI: 83–244 percent, p < 0.001).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Sex differences in mortality by occurrence of MI
In this elderly population, the occurrence of MI during follow-up decreased survival disproportionately in women compared with men. In the group that did not experience an MI, the survival advantage of women was remarkably similar to that described for other elderly cohorts (31Go) as well as younger populations (32Go, 33Go). After the occurrence of MI, on the other hand, women had only a small, nonsignificant advantage compared with men in multivariable analysis.

These findings are consistent with previous studies of follow-up of elderly MI patients. In the elderly, in contrast to younger patients, no sex differences in mortality after MI are usually found in the short term (34Go, 35Go). With prolonged follow-up after MI (longer than 1 year), women, especially older women, tend to show improved survival in most studies that have adjusted for baseline differences, particularly when early deaths are excluded (1GoGoGoGoGoGoGoGoGoGoGoGo–13Go).

Population perspective
When long-term mortality of men and women after MI is considered in the context of the mortality experience of those who did not develop an MI, sex differences are clarified. The 13 percent lower mortality of women in the hospitalized MI group compared with men was significantly smaller than what was observed in the absence of an MI. When out-of-hospital infarctions were included in the analysis as MI cases, mortality was actually 23 percent higher in women than in men among the MI cases. Therefore, MI is a stronger risk factor for death in elderly women than in elderly men, and it narrows the sex gap in survival. The lower long-term mortality in women observed in several studies is mostly a reflection of women's greater life expectancy rather than an indicator of a less-adverse impact of MI on their long-term mortality.

By taking into account the mortality of older adults who never experienced an MI, our study shows an alternative way of examining sex differences in long-term survival after MI. Since the life expectancy of men and women differs, this approach provides a clearer understanding of the relative impact of MI on the survival experience of women and men. Had we not considered the mortality of subjects without a history of MI (at each time point during follow-up), we would have concluded that MI had a similar or perhaps slightly smaller effect on women's survival compared with men's given the lack of association between sex and mortality in the MI group. However, by considering the mortality experience of those who, at each time point, had not experienced an MI, we were able to recognize the disproportionate effect of MI on survival in women.

A population-based approach similar to ours has given insight on sex differences in mortality for diabetes, showing that diabetes clearly erases the female advantage (36Go). Similarly, Framingham Study investigators have demonstrated that atrial fibrillation imposes a greater burden on mortality for women, revealed by comparison with those without atrial fibrillation (37Go). In addition, similar procedures considering expected survival are commonly used in cancer epidemiology (16Go). However, to our knowledge this approach has not been used when comparing sexes regarding long-term mortality after MI.

Possible mechanisms
An interpretation of the greater mortality burden associated with MI in older women is that MI has a more adverse effect in older women than in older men. A possible explanation might be the higher rates of CHD risk factors, diabetes, and stroke in women who experienced an MI compared with men, which put women at higher risk of more severe infarctions and/or of MI-related complications. Higher prevalence rates of comorbidity and risk factors for female MI patients have been reported fairly consistently (38GoGoGo–41Go) and were found in this study as well. In our study, however, adjustment for CHD risk factors and comorbidity had a negligible effect on the sex estimates, both in the presence and absence of MI. Therefore, the greater impact of MI on survival in women relative to men cannot be attributed solely to these factors. Obviously, unmeasured comorbidity might account for part of the sex differences found here. Another potential explanation for the more adverse effect of MI in women is decreased efficacy of some therapeutic modalities in women, specifically, thrombolytics and aspirin (42Go), although data from randomized trials of thrombolytic therapy do not clearly indicate that women benefit less than men from this treatment (38Go, 43Go). Finally, a tendency toward underutilization of established treatments for MI by women relative to men (10Go, 42Go, 44Go, 45Go) may play a role. While these mechanisms warrant further study, they could not be considered in the present analysis since they apply to only the MI group.

A second way to interpret our findings is that MI has an "equalizing effect" on survival; that is, the occurrence of MI makes the sexes equally susceptible to death. In our study, the higher hazard for mortality associated with MI in women appears to be largely a function of their superior survival in the absence of MI rather than of higher mortality rates in female versus male MI subjects, suggesting such an equalizing effect. The fundamental implication is that MI, for yet unknown reasons, reduces the natural protection that women have even at an older age in a way similar to that described for diabetes (36Go) and atrial fibrillation (37Go). In the past, it has been argued that overt CHD would abolish women's survival advantage over men (46Go). This argument was based on the finding of a higher case fatality rate for MI in females compared with males in one of the earliest publications on this topic (46Go). However, after the acute post-MI phase, women might still be able to catch up to their typical survival advantage, as their better long-term survival suggests (47Go). Consequently, a longer follow-up period, together with reference population mortality rates, is required to assess whether women's greater life expectancy compared with men's is truly affected by MI. Our results from an elderly cohort indicate that after MI, women do not completely catch up to their survival advantage. We therefore confirmed this earlier suspicion by using a more rigorous approach.

A third possible explanation for our findings is that more men than women with coronary events die out of the hospital. If men are more likely to die before they reach the hospital (and therefore before they can receive a diagnosis of MI), the mortality of men classified as free of MI, relative to women, might be inflated artificially. A study from the Scottish MONICA project found that out-of-hospital CHD deaths were more common in men than in women, therefore arousing this suspicion (48Go). A report from another MONICA center, Auckland in New Zealand, confirmed this finding (49Go). However, a recent study based on the whole MONICA registry involving 29 populations in 18 different countries found similar median rates of prehospital death in men and women, with substantial variation in rates across countries (50Go).

A considerable strength of our study was our ability to rule out a possible higher rate of out-of-hospital deaths in men as a potential source of bias in our results. In our study, neither all-cause nor CHD-specific out-of-hospital mortality was higher in men. On the contrary, out-of-hospital CHD mortality tended to be higher in women, particularly in the group never admitted for MI. When accounted for as MI events, these fatal MIs increase the impact of MI on mortality in women relative to men. The observed slightly higher out-of-hospital CHD cumulative mortality rate in women may be due to a higher frequency of unrecognized MIs in women than in men (51Go). It should be noted that classification of causes of death in our study was based on death certificates, whose accuracy has been questioned (24Go), particularly for the elderly (25GoGo–27Go) and nursing home residents (27Go). Therefore, our results of slightly higher out-of-hospital CHD mortality in women should be considered with caution.

Strengths and limitations
A major advantage of our investigation was the availability of population-based data, which provided us with a reference population for the MI cases as well as with information on out-of-hospital mortality. Another important strength of our study was surveillance of hospitalizations, which supplied information on the occurrence of MIs that met standard diagnostic criteria.

A limitation of our study is that it was performed in a single community; therefore, the generalizability of our findings to other communities is uncertain. Nonetheless, our cohort is diverse in terms of racial and socioeconomic backgrounds (17Go) and therefore is likely to be representative of many other US communities. Another limitation is that our sample included persons only >=65 years old. However, MI in women occurs mostly at older ages, and the overall survival advantage of women over men in our cohort was very similar to that reported in younger cohorts (32Go, 33Go). Sex differences in mortality after MI are most marked in younger patients (34Go, 35Go). Therefore, if younger patients had been included, our finding of a greater mortality burden of MI in women would have been even more marked. Finally, the number of MI events was somewhat small in our study. Nonetheless, given the large number of deaths, this study had sufficient power to detect a significant interaction between sex and MI. The power to detect significant sex differences within the MI group was more limited, as denoted by the larger confidence intervals in the MI group shown in table 2. However, our aim was to examine the interaction effect (i.e., whether the effect of sex varied according to the presence or absence of MI) rather than to assess the effect of sex among MI subjects, which has been addressed previously (1GoGoGoGoGoGoGoGoGoGoGoGoGo–14Go).

In conclusion, in this elderly cohort, we considered women's longer survival in the absence of MI and demonstrated a greater long-term mortality burden of MI in women than men. Our approach reveals that, even if there are no sex differences in mortality after MI or women have lower rates, MI is a stronger risk factor for mortality in women than in men, and it narrows women's typical survival advantage.


    ACKNOWLEDGMENTS
 
This study was supported in part by contract N01-AG-02105 from the National Institute on Aging and by Donaghue Medical Research Foundation grant 95-094.


    NOTES
 
Reprint requests to Dr. Viola Vaccarino, Department of Epidemiology and Public Health, Yale University School of Medicine, 60 College Street, PO Box 208034, New Haven, CT 06520-8034 (e-mail: viola.vaccarino{at}yale.edu).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication June 21, 1999. Accepted for publication February 14, 2000.