1 Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC.
2 College of Pharmacy, University of Minnesota, Minneapolis, MN.
3 Department of Medicine, Duke University Medical Center, Durham, NC.
4 Center for Health Services Research in Primary Care, VA Medical Center, Durham, NC.
5 Geriatric Research, Education and Clinical Center, VA Medical Center, Durham, NC.
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ABSTRACT |
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blacks; cognition; estrogen replacement therapy; longitudinal studies; whites; women
Abbreviations: EPESE, Established Populations for Epidemiologic Studies of the Elderly; SPMSQ, Short Portable Mental Status Questionnaire.
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INTRODUCTION |
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Of the larger population-based reports, a study of 800 well-educated, primarily White women aged 6595 years, three quarters of whom had used estrogen, found no association between estrogen use and performance on tests of cognitive function (11). A study of over 3,000 women aged 65 years or more enrolled in the Study of Osteoporotic Fractures produced unexpected findings with respect to time of estrogen use (compared with no use, past use was protective and present use was not) and inconsistent findings regarding different measures of cognitive function (12
). The authors of this study attributed protective effects to characteristics of the subjects rather than to pharmacologic intervention. However, another study that followed over 500 African-American, Hispanic, and White women (13
), just over 10 percent of whom had used estrogen (and then comparatively briefly), found improvement over time on tests of verbal memory among estrogen users compared with decline among nonusers. The paucity of population-based studies and the lack of control in most studies for characteristics other than demographic variables that may affect cognitive function (e.g., medication use, health conditions) make it unclear whether postmenopausal use of estrogen protects cognitive function and, if so, whether it is protective regardless of duration of use or time of use in relation to cognitive testing (1
, 3
, 4
).
The present cohort study examined the impact of estrogen use after menopause on the future level of cognitive function in a representative sample of older community-resident women who were cognitively intact at the start of the study. In particular, we distinguished whether the effect (if present) differed according to whether use was recent or occurred in the past or was continuous as opposed to intermittent. Our analysis controlled, in succession, for demographic characteristics and identified covariates.
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MATERIALS AND METHODS |
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In brief, a stratified, random household sample (African Americans were oversampled to improve statistical precision) was drawn. Of those sampled, 80 percent (4,162) agreed to participate, of whom 2,705 were women. In the analyses, sampling weights were used to adjust for the oversampling, differential sampling probabilities by household size, and nonrandom nonresponse. The subjects for the present study were those women whose level of cognitive function at baseline was unimpaired according to the Short Portable Mental Status Questionnaire (SPMSQ) (16) and who survived to the second in-person wave 3 years later. All were tracked to the third in-person wave 6 years later, but some women died in the interim.
Data-gathering procedures
Subjects were contacted annually between 19861987 (baseline) and 19921993, and in-person interviews were carried out triennially. During the in-person interviews, information was gathered on demographic characteristics, health status, health conditions, and health behaviors. The SPMSQ (15) was administered. At wave 1 (baseline), subjects were asked, "Around the time of your change of life or menopause or anytime since then, have you been treated with estrogen or female hormones?" If they answered yes, they were asked the following question: "Did you take them for more than 2 years?" In addition, at each triennial in-person wave, information was obtained on medication use. Information on the name of the drug, dosage form, and dose was copied from the medication label; the respondent indicated whether the drug had been taken in the previous 2 weeks and how much had been taken the previous day. Drug data entry was computerized by using a system found to be highly reliable. The rate of coding errors, based on reentry of a 5-percent sample of drugs, was estimated to be 1.63 percent (95 percent confidence interval: 0.71, 2.55) (17
).
Outcome measures.
Level of cognitive function was assessed by means of the SPMSQ, a brief, valid, reliable (test-retest Pearson r = 0.82), and commonly used screen developed for use among community residents (16). The SPMSQ may be the only race- and education-fair cognitive screen currently available (18
). Uniquely, it does not over-identify African Americans or those persons with less education as cognitively impaired or demented. The specificity and sensitivity of this measure in this population are 89.9 and 89.6 percent, respectively, for African Americans and 90 and 100 percent, respectively, for Whites (18
). This 10-item measure focuses on orientation, memory, and concentration. It can be scored in terms of the number of errors made or, by using a race and education adjustment, to indicate the presence or absence of cognitive impairment.
For purposes of our analysis, two dependent variables were created. The first measured the development of cognitive impairment as determined by an increase in errors resulting in transition, across a scoring threshold, to impaired cognitive function. Specifically, separate cutpoints (number of errors made) distinguished cognitively intact from cognitively impaired status for each of six groups of persons: African Americans aged 65 years or more with 08, 912, and more than 12 years of education and Whites of the same age in the same educational categories. White elderly with 912 years of education were considered cognitively impaired if they made three or more errors on the SPMSQ. White elderly with more education were permitted one error less (i.e., they were considered cognitively impaired if they made two or more errors), and Whites with less education were permitted one error more. In each education category, African-American elderly were permitted one error more than White elderly before reaching the cognitive impairment threshold. Among those initially cognitively intact, incident cognitive impairment occurred when the number of errors made on later testing (wave 2 or wave 3) reached or passed the cognitive impairment threshold.
The second dependent variable was an increase of two or more errors on the SPMSQ (i.e., deterioration in cognitive performance). Previous work (19) determined this to be a clinically meaningful change that predicted decline in functional status.
Estrogen exposure.
Exposure to estrogen was determined from computerized files of participants' prescription drug data coded by using an updated and modified version of the Drug Product Information Coding System (20, 21
). Exposure to estrogen was operationally defined by three indicator variables, as follows: 1) recent use (use at wave 1 when predicting cognitive change from wave 1 to wave 2, and use at wave 2 when predicting cognitive change from wave 2 to wave 3); 2) past use (use before wave 1 when predicting cognitive change from wave 1 to wave 2, and use no more recently than wave 1 when predicting cognitive change from wave 2 to wave 3); and 3) nonuse (no history of estrogen use). To evaluate the possibility of a duration- response relation, duration was operationally defined as either continuous or intermittent use. Continuous use was defined as use both at wave 1 and for 2 or more years before that when predicting cognitive change from wave 1 to wave 2, and use at wave 1 and wave 2 when predicting cognitive change from wave 2 to wave 3. Intermittent use was defined as use at wave 1 or prior to wave 1 when predicting cognitive change from wave 1 to wave 2, and use on two occasionswave 2 and prior to wave 1, or wave 1 and prior to wave 1when predicting cognitive change from wave 2 to wave 3. Those women who never used estrogen were the reference group.
Control variables
We adjusted for potential confounding variables that may influence the relation between cognitive status and estrogen use. All covariates, unless otherwise indicated, were measured at wave 1. Examined were demographic characteristics (age, education, race, marital status, number of natural children (13, 22
24
)); health-related behaviors (body mass index (based on self-reported height and weight (25
)), smoking status, and alcohol consumption (26
, 27
)); selected medications that may influence cognitive impairment (thyroid, benzodiazepine, nonsteroidal anti-inflammatory drugs (28
31
)) or that are taken for one of the same reasons as estrogen (e.g., calcium); health conditions (self-report of physician-diagnosed stroke, diabetes, hip fracture, other broken bones, arthritis (information obtained at wave 2 only), heart attack, hypertension, incontinence, self-rated health (32
)); health status as assessed by using the abbreviated Rosow-Breslau physical health scale (33
) and the Older Americans Resources and Services scale of instrumental activities of daily living (34
, 35
); and depression as measured by the Center for Epidemiologic Studies Depression Scale (36
, 37
). In the Duke EPESE, the depression scale items were dichotomous. A score of 9 or more on this scale has been shown to be equivalent to a score of 16 or more on the original Center for Epidemiologic Studies Depression Scale (15
) and is indicative of clinical depression. All variables are described fully in table 1.
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We assumed this to be the case when an item was answered by nearly all subjects (defined here as over 98 percent). We further assumed these subjects to be comparable to the group as a whole and so assigned as a score the mean value for the variable. For items with 25 percent missing data, we assumed that people with certain characteristics (e.g., increased age, less education, female gender) might be less inclined to respond, that is, that nonresponse was not random but reflected a bias, which might vary with each item. In that situation, we considered all of the other independent variables in the model and assigned a regression-predicted score (41). If 5 percent or more of the data were missing, we extended this approach and used the predictive mean matching method (38
), a stochastic regression technique for imputing missing data. Stochastic imputation (the imputation of an error term along with a predicted score) is designed to estimate the variance as well as the mean of the imputed variable with accuracy and therefore to minimize bias in relevant tests of significance (39
, 42
). Prior to imputation, significance tests were adjusted to reflect the number of nonmissing cases (43
).
Statistical analysis.
The analysis proceeded in three phases. In the first phase, the data were summarized by percentages or means for all covariates (table 1). In the second phase, we ran univariate analyses to determine an association with each cognitive measure. In these initial analyses, quadratic terms were used to test for nonlinearities in the effects of each continuous independent variable on each measure of cognitive change. On the basis of findings of nonlinear effects, dummy variables were used to contrast those respondents in the middle and upper income categories with those whose annual income was less than $3,500. For incident cognitive impairment only, the effects of education were also nonlinear and were represented by a set of dummy variables. The effects of body mass were also nonlinear and were represented by a squared as well as a linear term in the analyses. About 80 percent of respondents were nondrinkers, and most others drank in moderation. This finding limited our statistical power to detect the effects of problem drinking. The time-varying depression and smoking measures referred to depression and smoking at baseline or a period at risk.
The third phase of the analysis involved constructing three-stage multivariable models in which controls were added for baseline SPMSQ score (stage 1), demographic characteristics (stage 2), and health and health-related behaviors (stage 3). Demographic measures were retained as controls in all models, as were measures of health-related behaviors and medications. For each dependent variable, measures of health were retained if they remained significant after we controlled for demographics, health-related behaviors, and each of the other measures of health. Discrete-time hazards models (44, 45
) were used for the longitudinal analysis of the first occurrence of decline among those who were not disabled at wave 1. Discrete-time models closely approximate the Cox proportional hazards model and (unlike the standard Cox model) can be used when the timing of an event is discrete rather than continuous. Respondents contribute an observation for each "interval" (period between waves) at risk until their decline, their death, or censoring at the end of the study period (45
). These intervals become the units of analysis in a person-years data set (46
). While logistic regression is used to estimate the coefficients, use of the person-years data set takes the timing of an event and right censoring into account, and the results closely approximate those obtained by using the Cox proportional hazards model (44
, 45
) rather than a standard logistic incidence model. In the analysis, we removed respondents who died during the course of the study from the risk set estimating models for cognitive impairment and decline. As discussed by Allison (45
), dropping those who died is equivalent to treating death as a competing risk, in that those who die are no longer at risk of decline or impairment. All data were weighted to adjust for the sampling design and to permit inference to the five-county area. Significance tests were performed by using SUDAAN (47
), a specialized software program that adjusts for clustering and stratification in the sampling design.
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RESULTS |
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The results of the multivariable models are presented in table 4. For each of the two dependent variables (development of cognitive impairment, increase of two or more errors on the SPMSQ), we examined two alternative ways of considering estrogen use: recent and past use compared with no use, and continuous and intermittent use compared with no use. In each case, a three-stage model was used. In the first stage, we entered SPMSQ score at baseline to control for differences in level of cognitive function on the SPMSQ and, in particular, to account for scores close to the impaired/not impaired cutpoint on the SPMSQ. The odds ratios obtained from these analyses (stage 1) suggested that use of estrogen for 2 years or more protects cognitive function. Regardless of whether use was recent (within the past 3 years) or past (6 or more years previously) or was continuous or intermittent, compared with those who reported no use of estrogen, cognitive impairment was less likely to occur, and the number of SPMSQ errors was less likely to increase. Such positive effects were stronger for those women using estrogen more recently or more consistently. This positive effect, however, was rarely statistically significant.
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The addition of health-related variables (stage 3) further attenuated the association of estrogen use with level of cognitive function. While point estimates for recent and continuous users continued to suggest a protective effect, no protective effects remained for past or intermittent users, and none of the associations was statistically significant.
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DISCUSSION |
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When potential covariates were included in the model, the effects of estrogen use were markedly attenuated, indicating the importance of demographic characteristics, health behaviors, health conditions, and health status in affecting cognitive function. The association of such characteristics with cognitive function has long been recognized on a cross-sectional basis, although it has not always been well established longitudinally (2426
, 31
, 32
, 35
, 37
, 48
, 49
).
Our results agree with those from other community-based studies that have been unable to confirm the protective effect of estrogen on cognitive function (10, 11
, 49
), but they do not agree with those of Jacobs et al. (13
). This discrepancy may reflect our inclusion of additional covariates, such as health-related variables, in our analysis. Such characteristics, which have been shown to affect cognitive performance, have typically not been controlled in prior studies. While we found that demographic characteristics alone reduced the relation of estrogen use to cognitive function, the addition of health characteristics further attenuated the relation. This finding suggests that to maintain cognitive function in older women, careful attention should be paid to these characteristics. Of the demographic characteristics studied, only one, education, is amenable to intervention. Regardless of whether increased education reduces the risk of cognitive decline, it is related to other desirable outcomes, such as improved socioeconomic and health status (23
).
A basic concern inherent in the present study is the small proportion of women (21 percent) who used estrogen for a minimum of 2 years and the even smaller proportion who were consistent, long-term users (5 percent). These proportions compare with use by about 40 percent of the women, all White, enrolled in the Study of Osteoporotic Fractures (12), all of whom were volunteers. Our small percentages of estrogen users adversely affected statistical power and our ability to detect significant effects. Nevertheless, our proportions were about twice as large as those reported by Jacobs et al. (13
).
Estrogen use varies by race and socioeconomic status and may be influenced by the medical care setting (49). Handa et al. (50
) found that users tended to be younger, be White, be more affluent, have smaller families, take calcium supplements, and live in an urban area. Those who were older, were Black, had more children, and drank no alcohol were more likely to cease using estrogen. Similarly, Matthews et al. (12
), in their White volunteer population, found that estrogen users were younger and better educated. They were also more likely to be using thyroid hormones and sedatives or anxiolytics. In our study, only 1 percent of African-American women were using estrogen at wave 1, although 10 percent had used it earlier. Because of this low rate, we did not examine race interactions.
Estrogen use may reflect secular trends in prescribing estrogen and the particular health care environment. In our sample of women up to 100 years of age, many entered menopause before the prescribing of estrogen was encouraged or possibly even discussed. Few, if any, were members of a health maintenance organization and so were less subject to managed care's emphasis on prevention of health problems.
Unlike in most previous studies, the present study collected data from a population-representative sample that included both African-American and White women in urban and rural areas at all levels of the socioeconomic spectrum. Contact was maintained at annual intervals, and attrition for reasons other than death was minimal. Nevertheless, since all women lived in a restricted geographic area, the findings may not be broadly generalizable. Although type of estrogen replacement therapy and dose were recorded during the study, such information was not available on use prior to study entry, so the effect of dose intensity could not be examined. Neither did we gather precise information on duration of use of estrogen, although information on use at each data-gathering occasion permitted reasonable estimation of duration of use.
An additional limitation is the cognitive measure that was available. While the SPMSQ is an adequate survey screen to identify those persons whose cognitive status is impaired, and in that use is race and education fair, it is not a targeted measure of memory or of other areas of cognitive function. Thus, we were unable to determine whether estrogen use has a specific impact on alternative areas of cognitive function. The SPMSQ is, however, comparable to the modified Mini-Mental State Examination (51). With that measure, no consistent protective effect of estrogen use was found (12
). Furthermore, there is a ceiling effect on the SPMSQ; that is, in the present sample, which excluded the cognitively impaired, 54 percent of the women made no errors. Consequently, the impact of estrogen use cannot be examined readily among those women with a high cognitive capacity. While test-retest data indicate that the SPMSQ is a reliable measure (r = 0.82 (16
)), the unreliability that does exist may attenuate the findings.
Such caveats notwithstanding, the present study was prospective and not cross-sectional, and it included a more representative sample of cognitively intact, community-resident women than has been examined to date. Our focus was on change in cognitive function, not on development of Alzheimer's disease (15
, 49
). Whether estrogen use is protective with respect to that disorder may be determined by two major clinical trials: a randomized control study within the Women's Health Initiative Memory Study (52
), examining the association of estrogen with development of dementia, and the Alzheimer Disease Cooperative Study Unit trial funded by the National Institute on Aging (7
), examining the impact of estrogen on the cognitive function of women with Alzheimer's disease. A recent report from the latter trial indicates that estrogen replacement therapy taken for 1 year does "not slow disease progression" nor "improve global, cognitive or functional outcomes in women with mild to moderate AD [Alzheimer's disease]" (7
, p. 1007).
Our data suggest that, in controlled analyses, estrogen does not have a statistically significant protective effect on cognitive function in unimpaired women. It may, however, be one of a variety of variables, some of which are susceptible to intervention, that merit further exploration to identify factors that affect cognitive function.
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ACKNOWLEDGMENTS |
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The content of this paper does not necessarily reflect the views or policies of the US Department of Health and Human Services nor does mention of trade names, commercial products, or organizations imply endorsement by the US government.
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NOTES |
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REFERENCES |
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