Published online before print October 4, 2004, doi: 10.1161/01.HYP.0000145858.07252.99
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
(Hypertension. 2004;44:631.)
© 2004 American Heart Association, Inc.
Scientific Contributions |
Blood Pressure-Related Cognitive Decline
Does Age Make a Difference?
From the Department of Psychology (P.K.E., M.F.E., M.A.R), University of Maine, Orono; Statistics and Consulting Unit (P.K.E., M.F.E.), Department of Mathematics and Statistics, Boston University, Boston, Mass; Department of Geriatric Medicine (M.M.B), ANU Medical School, The Canberra Hospital, Woden ACT, Australia.
Correspondence to Penelope K. Elias, PhD, Department of Psychology, University of Maine, Orono, ME 04469. E-mail PElias100{at}aol.com
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Systolic and diastolic blood pressures have been inversely related to cognitive performance in prospective and cross-sectional studies. However, in large, community-based samples, these findings have been limited to older adults. In this 20-year longitudinal study, we examined the relationship between baseline blood pressure and cognitive decline for 529 participants using 2 age groups (18 to 46 years and 47 to 83 years). Cognitive performance was measured over multiple examinations with the Wechsler Adult Intelligence Scale from which 4 scores were derived by factor analysis. A 2-stage growth curve method of analysis was used to model cognitive change. Results indicated that higher levels of baseline systolic blood pressure, diastolic blood pressure, mean arterial pressure, and blood pressure categories as defined by the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure were significantly associated with decline in Visualization/Fluid abilities in both younger and older age groups. Young adults are as susceptible to blood pressure-related longitudinal decline in cognitive performance as are older adults.
Key Words: blood pressure • age • arterial hypertension • cognition • prospective studies • risk factors
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Hypertension is related to poorer cognitive performance in adults,1,2 and hypertension-related changes in the brain are well-documented.3–9 Systolic blood pressure (SBP) and diastolic blood pressure (DBP) levels have been inversely related to cognitive performance level.2,10,11 Moreover, DBP and SBP levels in midlife have been inversely associated with performance levels on cognitive tests administered at later ages.9,12–14
It is important to determine whether baseline BP values are associated with accelerated cognitive change with advancing age. Longitudinal designs are methodologically superior to cross-sectional designs because BP level can be related to intra-individual decline in cognitive functioning.15,16 Most of the longitudinal studies using large, community-based samples have involved only midlife or older individuals.17–20 Recently, Knopman et al studied persons ranging in age from 47 to 70 years and found that hypertension was related to cognitive decline from baseline to 6-year follow-up, but only for persons aged 58 to 70 years.21
In contrast to longitudinal findings, cross-sectional studies indicate that younger adult hypertensive individuals may be more vulnerable to BP-related decrement in cognitive functioning than older hypertensive individuals.10,22 This phenomenon may be an artifact of cross-sectional designs.1,2,10 However, the possibility that younger adult hypertensive individuals exhibit greater cognitive decline than older hypertensive individuals has not been tested with a longitudinal design that included persons younger than 47 years of age. The major objective of the present study was to compare older and younger adults with respect to BP-associated cognitive decline using a prospective longitudinal design with multiple examinations and participants with a wide age range (18 to 83 years). Based on the longitudinal literature, we hypothesized that cognitive decline in relation to baseline BP would be greater for older than for younger adults.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Participants
The subjects were participants of the Maine–Syracuse Longitudinal Study of Hypertension (MLSH) who were administered the Wechsler Adult Intelligence Scale (WAIS)23 and a hypertension diagnostic examination at baseline and at subsequent examinations (please see http://hyper.ahajournals.org).
Individuals with dementia, stroke, alcoholism, drug abuse, or psychiatric illness diagnosed were not eligible for baseline testing. Of the 1019 eligible study participants, 834 were invited to participate in the longitudinal study. Of the 834 invited participants, 305 were lost for the following reasons: died (n=68), refused (n=149), too ill to participate (n=16), too distant to be reached (n=46), and did not reply to contact (n=26). The 529 remaining subjects provided baseline data for the present study.
Participants either had no antihypertensive drug treatment history at baseline (n=296) or, if previously treated (n=233), were requested to withdraw from treatment (under their physician’s supervision) 14 to 21 days before baseline testing. The BP profiles used for the present analyses were based on an average of 6 sitting, 6 reclining, and 6 standing BP measurements conducted at baseline. Blood pressure was measured with a Critikon Dinamap 1846SX automated BP monitor. Hypertension was defined as SBP
140 mm Hg and/or DBP90 mm Hg.
A time-lagged, cohort-sequential design was used, ie, 4 cohorts defined on the basis of the year that baseline testing was accomplished were followed longitudinally for 4 (cohort 1), 3 (cohort 2), 2 (cohort 3), and 1 (cohort 4) examinations beyond baseline. Data on number of participants throughout the course of the study are shown in Table 1.
|
After baseline testing, the 529 longitudinal participants were tested as follows: 283 were tested once, 132 tested 2 times, 58 tested 3 times, and 56 tested 4 times within the 20-year study period (mean time between examinations=5.2 years, SD=0.63 years).
Mean age was 46 years. To maximize the balance in numbers of subjects in the older and younger groups, we established an age of 46 as the upper limit for our younger group and 47 as the lower limit for our older group. Thus, the ages of all individuals in our young group were younger than 47 years, the lower age limit of the subjects in the Knopman et al21 study. Consequently, we were able to examine longitudinal BP–cognitive relationships for younger adults in a relatively unexplored age range. There was no statistically significant difference in number of times tested for the younger and older participants (P>0.05).
The study was approved by the University of Maine and The State University of New York (SUNY) Upstate Medical University Institutional Review Boards. Informed consent for participation was obtained in writing before data collection.
Dependent Variables
The WAIS23 was administered at each longitudinal examination and included the following subtests in a verbal scale (Information, Vocabulary, Comprehension, Arithmetic, Digit Span, and Similarities) and a performance scale (Picture Completion, Object Assembly, Block Design, Picture Arrangement, and Digit Symbol Substitution). To achieve variable reduction and theoretically meaningful summary scores of abilities measured by the WAIS, we used 4 scores based on extensive factor analytic studies in previous investigations.24,25 These scores were as follows: (1) Crystallized/Verbal (Comprehension, Similarities, Vocabulary, and Information); (2) Visualization/Fluid (V/F) (Picture Completion, Picture Arrangement, Block Design and Object Assembly); (3) Memory (Arithmetic, Digit Span Forward and Digit Span Backward); and (4) Speed (Digit Symbol Substitution).
Each WAIS subtest score was expressed as a percent correct score, ie, the number of points correct was divided by the total possible number of points. The 4 composite scores were derived by adding the subtest scores (percent correct) within a composite and dividing by the number of subtests in that composite.26
Predictor Variables
Five mean BP variables were calculated from the 18 measurements obtained at baseline: (1) DBP; (2) SBP; (3) pulse pressure (PP), calculated as SBP–DBP; (4) mean arterial pressure (MAP), calculated as MAP=DBP+PP/3; and (5) BP classification based on the criteria of the Seventh Report of the Joint National Committee (JNC) on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure,27 ie, 4 ordinal categories: Normal, defined as SBP <120 mm Hg and DBP <80 mm Hg; Prehypertension, defined as SBP=120 to 139 or DBP=80 to 89; Stage I Hypertension, defined as SBP=140 to 159 or DBP=90 to 99; and Stage II Hypertension, defined as SBP160 or DBP100.
Covariates
Regression models included the following covariates: (1) age (years at baseline); (2) education (years at baseline); (3) occupation (highest level); (4) gender; (5) alcohol use (drinks/d, averaged over all examinations); (6) cigarettes/d (averaged over all examinations); (7) psychotropic medication use during the study (yes=1 or no=0); (8) body mass index (averaged over all examinations); and (9) Zung depression scale scores (averaged over all examinations). Age (in years) at baseline was included among the covariates because it might be expected to have a confounding effect via both BP levels and cognitive performance regardless of age range of the sample.
In secondary analyses, subjects with a history of, treated for, or diagnosed with 1 or more coexisting diseases at any point in the study were excluded. These included subjects with type I or type II diabetes (n=53), other major diseases such as cancer (n=9), and hypertension-related complications, ie, coronary artery disease, myocardial infarction, transient ischemic attack, stroke, kidney disease (n=52).
Statistical Analyses: Measurement of Cognitive Change
A 2-stage growth curve method was used.28 This method does not require equal numbers of participants at each examination or equal time intervals between serial examinations. Data for all subjects who completed at least 2 longitudinal examinations, including the baseline examination, are used to estimate missing longitudinal data.28–30 Longitudinal attrition is controlled statistically because all the longitudinal data are used in the estimates of cognitive change over time.
For stage 1, a linear model was fit to the each of the WAIS composite scores for each individual using the method of least squares: Yit=ai+biti+eit. For each individual (i) at occasion of testing (t), Y is the observed test score, a is the intercept, and b is the raw regression coefficient for test scores regressed on time (t). Because each individual’s test scores over time are regressed on number of years from point of entry into the study (defined as 0), the intercept value (a) is each individual’s estimated test score at entry into the study (examination 1) and the slope value (b) is each individual’s estimated longitudinal change over time. Change over time was expressed in 1-year intervals of longitudinal study participation. Thus, every study participant received 2 scores in stage 1 analyses: (1) an intercept score representing estimated baseline performance; and (2) a slope score representing estimated change in performance over 1 year of study participation.
The slope values (cognitive change scores) were the dependent variables for stage 2 of the analysis. However, intercepts were included in all stage 2 regression models to control for estimated baseline performance.
Regression Analyses
For stage 2, multiple linear regression analyses were performed with the BP variables as the predictors and the estimated slopes as the dependent variables. Separate analyses were conducted for each combination of predictor (SBP, DBP, MAP, and PP in 10 mm Hg increments; JNC BP classification expressed as 1, 2, 3, 4 ordinal scale) and dependent variables (Crystallized/Verbal, V/F, Memory, and Speed scores).
These multiple regression analyses resulted in raw regression coefficients (ß) expressing independent statistical associations between each of the covariables and the slope values for the WAIS composite scores. A weighted least-squares analysis was used to allow slope values estimated with more precision to be weighted more than those with larger standard errors.30
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Table 2 displays the demographic and health characteristics of the participants. Baseline and mean (all examinations) SBP and DBP, the prevalence of hypertension at baseline, hypertension at any examination, and number of comorbid diseases were higher for the older individuals. A modestly larger percentage of young hypertensive persons than older hypertensive persons received treatment when referred back to their physicians.
|
Subjects lost before examination 2 were lower in occupation (4.5 versus 5.1, P<0.001), younger (41.2 versus 45.6 years, P<0.001), and exhibited lower Crystallized/Verbal (69.2 versus 71.5, P<0.01) and Memory (69.5 versus 71.3, P<0.05) scores, but dropouts and those successfully recruited did not differ with respect to V/F or Speed scores.
Age Group Analyses
Baseline BP values were unrelated to cognitive change (slope scores) over time for the composites indexing Crystallized/Verbal Ability, Memory, and Speed. Consequently, we present results only for the V/F composite (Table 3).
|
The covariate-adjusted regression coefficients shown in Table 3 are the product of regressing individual cognitive change (slope) values on the baseline BP measures. Thus, the regression coefficients representing change in performance longitudinally are actually regression coefficients for the intra-individual slope values and can be interpreted in the following manner. The magnitude of the regression coefficient reflects the average intraindividual change in cognitive performance over time per increment in BP and the negative sign indicates the direction of the change (decrement).28
For V/F slopes, higher SBP, DBP, MAP, and JNC categories were associated with longitudinal decrement in performance for the younger and older groups. These relationships were observed when all study participants were included in the analyses and when persons with coexisting diseases were excluded.
PP also showed a significant association with the V/F composite for older participants only. The interaction of PP with age approached significance (P=0.09). However, when persons with coexisting disease were excluded from the analysis, the effect of PP was nonsignificant for both age groups.
To illustrate the linear trends in cognitive change, using MAP as an example, we dichotomized the continuous MAP values into 2 groups: MAP <105 mm Hg and MAP105 mm Hg.31 The estimated regression lines (adjusted for all covariates) for the younger and older age groups are shown in the Figure. Each regression line represents the estimated amount of change that would be expected over 20 years for the 2 age groups and MAP categories. Both younger and older age groups in the higher MAP category showed substantially more cognitive decline relative to their counterparts in the lower MAP category. When the dichotomous MAP variable was used in the full regression model, results for both the younger (ß=–0.307, P<0.05) and the older (ß=–0.423, P<0.03) groups were significant.
|
Interactions of age with the blood pressure measures were tested in 2 ways: age treated as a group variable (as in Table 3) and age treated as a continuous variable. All interactions were nonsignificant (P=0.09 to 0.99) and thus indicate that relations between BP variables and cognitive performance were substantially the same for younger and older study participants. However, SBP-related cognitive decline was modestly greater for the older than for the younger group (Table 3) and statistically significant only for the older group.
In summary, baseline BP and JNC classifications were associated with longitudinal decrement in performance on the V/F composite score. No significant BPxage interactions were observed for any of the cognitive measures.
Main Effects of Blood Pressure on Cognition
Because there was no significant agexBP interaction for the V/F composite, it is important to examine main effects. Table 4 presents the results for the association between BP variables and change in cognitive function for the sample with exclusions for coexisting disease. All baseline BP variables were associated with decline in cognitive performance with the exception of PP. There was no indication of poorer performance at the lower BP levels. Results were the same when participants with coexisting disease were included, except that now PP was significantly related to the V/F composite (ß=0.067; SEß=0.032, P<0.05). Neither days on antihypertensive drug holiday at baseline nor ever-treated versus never-treated with antihypertensive drugs during the longitudinal study was related to the cognitive outcome measures with the full set of covariates (P>0.05).
|
When individual components of the V/F composite were examined, it was found that Picture Completion (MAP, ß=–0.170, SEß=0.050; P<0.001), Block Design (MAP, ß=–0.133, SEß=0.048; P<0.01), and Object Assembly (MAP, ß=–0.111, SEß=0.059; P<0.05) were the primary tests accounting for the significant main effects. Results for SBP, DBP, and JNC categories showed similar significant relationships.
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
We tested the hypothesis that older adults would show greater BP-related cognitive decline than younger adults. The hypothesis was not confirmed by tests of the agexBP interactions. Further, with the exception of PP, the amounts of cognitive decline in V/F abilities associated with baseline BP shown by adults aged 18 to 47 and 48 to 83 were similar. Our data support the association between blood pressure and cognition for older study participants as shown by Knopman et al,21 and we have extended these findings to much younger adults. Our results were observed for adults exhibiting the normal range of cognitive functioning. No participants had dementia diagnosed throughout the course of the study and all participants were able to complete the test protocol.
Many cognitive abilities are affected by hypertension.1,2 However, findings of longitudinal BP–cognition relationships are often limited to tasks that index fluid abilities and executive function,10,32 as does our V/F composite. Our study indicates that higher baseline BP levels and JNC classifications are predictive of cognitive decline in V/F abilities, whereas Crystallized/Verbal, Memory, and Speed abilities are spared.
Our data and the findings by Knopman et al21 are consistent with the general conclusion that BP-associated performance deficits in nondemented, stroke-free individuals are relatively minor and manageable in terms of everyday functioning. For example, from the regression coefficient for the ordinal JNC scale (based on 1 year of change; Table 3), we see that moving from the "Normal" BP classification to the "Stage I Hypertension" classification (2 ordinal steps) would result in an estimated 8.12% decrement in correct responses on the V/F composite over 20 years. Commenting on findings from the ARIC study, Knopman et al21 observed that hypertension-related cognitive decline over 6 years was relatively small, and that its importance is with respect to marking potential pathophysiological changes in brain structure and function.
Study Limitations
Several study limitations most likely served to attenuate the estimated rate of longitudinal decline. Our subjects were relatively well-educated and concerned about treatment and their cognition. Further, persons lost to the study after baseline exhibited lower Crystallized/Verbal and Memory composite scores than those who provided longitudinal data. However, longitudinal change is generally not reported for the Crystallized/Verbal tests used in the present study10 and, whereas BP-related change in memory has been reported, tests used in these studies placed considerably more demands on working and episodic memory than tests that index the Memory component of the WAIS.1,2
Perspectives
The longitudinal changes that we see in young adults are consistent with a literature that indicates that the BP-related pathophysiological processes adversely affecting the brain may begin earlier in the adult lifespan than previously thought.1,2,10 The main importance of our findings lies at the population level. Blood pressure lowered by just 20 mm Hg SBP or 10 mm Hg DBP, or from "Hypertensive" to "Normal" JNC classification, would have a considerable beneficial effect on the preservation of cognitive abilities in the population as a whole. Given that younger adults appear at least as vulnerable to BP-related cognitive decline as are older adults, these benefits would be seen among young as well as middle-aged and older adults. It is important to continue and expand clinical trials relating the lowering of BP to cognitive performance. To the extent that BP effects on cognition are not reversible, it is important to prevent an increase in BP levels as early as possible in the life cycle.
|
Acknowledgments |
|---|
Preparation of this manuscript was supported by National Institute on Aging Project AG03055 and National Heart, Lung, and Blood Institute Project HL67358. We gratefully acknowledge Gregory Dore for his assistance in data reduction and tabular presentations.
Received March 22, 2004; first decision April 9, 2004; accepted July 28, 2004.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Elias MF, Robbins MA, Budge MM, Elias PK, Hermann BA, Dore GA. Studies of aging, hypertension and cognitive functioning, with contributions from the Maine-Syracuse Study. In: Costa PT, Siegler IC, eds. Advances in Cell Aging and Gerontology, Vol. 15, Recent Advances in Psychology and Aging. Amsterdam: Elsevier; 2004: 89–131.
2. Waldstein SR, Katzel LI. Hypertension and cognitive function. In: Waldstein SR, Elias MF, eds. Neuropsychology of Cardiovascular Disease. Mahwah, NJ: Lawrence Erlbaum Associates; 2001: 15–36.
3. Manolio TA, Olson J, Longstreth WT. Hypertension and cognitive function: Pathophysiologic effects of hypertension on the brain. Curr Hypertens Rep. 2003; 5: 255–261.[Medline] [Order article via Infotrieve]
4. de Leeuw FE, de Groot JC, Oudkerk M, Witteman JC, Hofman A, van Gijn J, Breteler MM. Hypertension and cerebral white matter lesions in a prospective cohort study. Brain. 2002; 125 (pt 4): 765–772.
5. Dufouil C, de Kersaint-Gilly A, Besancon V, Levy C, Auffray E, Brunnereau L, Alperovitch A, Tzourio C. Longitudinal study of blood pressure and white matter hyperintensities: the EVA MRI Cohort. Neurology. 2001; 56: 921–926.
6. Liao D, Cooper L, Cai J, Toole J, Bryan N, Burke G, Shahar E, Nieto J, Mosley T, Heiss G. The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: the ARIC Study. Neuroepidemiology. 1997; 16: 149–162.[Medline] [Order article via Infotrieve]
7. Longstreth WT, Manolio TA, Arnold A, Burke GL, Bryan N, Jungreis CA, Enright PL, O’Leary D, Fried L. Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: The Cardiovascular Health Study. Stroke. 1996; 27: 1274–1282.
8. Breteler MM, van Swieten JC, Bots ML, Grobbee DE, Claus JJ, van den Hout JH, Harskamp F, Tanghe HL, de Jong PT, van Gijn J. Cerebral white matter lesions, vascular risk factors and cognitive function in a population-based study: the Rotterdam Study. Neurology. 1994; 44: 1246–1252.
9. Swan GE, DeCarli C, Miller BL, Reed T, Wolf PA, Jack LM, Carmelli D. Association of midlife blood pressure and late-life cognitive decline and brain morphology. Neurology. 1998; 51: 986–993.
10. Waldstein SR. Hypertension and neuropsychological function: A life-span perspective. Exp Aging Res. 1995; 21: 321–352.[Medline] [Order article via Infotrieve]
11. Elias MF, Robbins MA, Schultz NR Jr., Pierce TW. Is blood pressure an important variable in research on aging and neuropsychological test performance? J Gerontol Psy Sci. 1990; 45: P 128–P135.
12. Elias MF, Wolf PA, D’Agostino RB, Cobb J, White LR. Untreated blood pressure level is inversely related to cognitive functioning. Am J Epidemiol. 1993; 138: 353–363.
13. Launer LJ, Masaki K, Petrovitch H, Foley D, Havlik RJ. The association between midlife blood pressure levels and late-life cognitive function. JAMA. 1995; 274: 1846–1851.
14. Swan GE, Carmelli D, Larue A. Systolic blood pressure tracking over 25 to 30 years and cognitive performance in older adults. Stroke. 1998; 29: 2334–2340.
15. Wilkie FL, Eisdorfer C. Intelligence and blood pressure in the aged. Science. 1971; 172: 959–962.
16. Waldstein SR. Heath effects on cognitive aging. In: Stern PC, Carstensen LL, eds. The Aging Mind. Washington, DC: Committee of Future Directions for Cognitive Research on Aging, Board on Behavioral, Cognitive and Sensory Sciences, Commission on Behavioral and Social Sciences and Education, National Research Council; 2000: 189–217.
17. Reinprecht F, Emståhl S, Janzon L, André-Petersson L. Hypertension and changes in cognitive function in 80-year-old men: a 13-year follow-up of the population study ‘Men born in 1914', Sweden. J Hypertens. 2003; 21: 57–66.[CrossRef][Medline] [Order article via Infotrieve]
18. Tzourio C, Dufouil C, Ducimetière P, Alpérovitch A, for the EVA Study Group. Cognitive decline in individuals with high blood pressure: a longitudinal study in the elderly. Neurology. 1999; 53: 1948–1952.
19. Prince M, Lewis G, Bird A, Blizard R, Mann A. A longitudinal study of factors predicting change in cognitive test scores over time in an older hypertensive population. Psychol Med. 1996; 26: 555–568.[Medline] [Order article via Infotrieve]
20. Glynn RJ, Beckett LA, Hebert LE, Morris MC, Scherr PA, Evans DA. Current and remote blood pressure and cognitive decline. JAMA. 1999; 281: 438–445.
21. Knopman D, Boland LL, Mosley T, Howard G, Liao D, Szklo M, McGovern P, Folsom AR, for the Atherosclerosis Risk in Communities (ARIC) Study Investigators. Cardiovascular risk factors and cognitive decline in middle-aged adults. Neurology. 2001; 56: 42–48.
22. Waldstein SR, Jennings JR, Ryan CM, Muldoon MF, Shapiro MF, Polefrone JM, Fazzari TV, Manuck SB. Hypertension and neuropsychological performance in men: Interactive effects of age. Health Psychol. 1996; 15: 102–109.[CrossRef][Medline] [Order article via Infotrieve]
23. Wechsler D. The Measurement and Appraisal of Adult Intelligence. Manual for the Wechsler Adult Intelligence Scale. New York: Psychological Corporation; 1955.
24. Horn J. Remodeling old models of intelligence. In: Wolman BB, ed. Handbook of Intelligence: Theories, Measurements, and Applications. New York: Wiley; 1985: 267–300.
25. Horn JL, McArdle JJ. Perspectives on mathematical statistical model building (MASMOB) in research on aging. In: Poon LW, ed. Aging in the 1980’s: Selected Contemporary Issues in the Psychology of Aging. Washington, DC: American Psychological Association; 1980: 503–541.
26. McArdle JJ, Hamagami F, Elias MF, Robbins MA. Structural modeling of mixed longitudinal and cross-sectional data. Exp Aging Res. 1991; 17: 29–52.[Medline] [Order article via Infotrieve]
27. Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Washington, DC: US Department of Health and Human Services; 2003: NIH Publication No. 03–5233.
28. Rogosa DR, Brandt D, Zimowski M. A growth curve approach to the measurement of change. Psychol Bull. 1982; 92: 726–748.[CrossRef]
29. Aldwin CM, Spiro A III, Levenson MR, Bossé R. Longitudinal findings from the Normative Aging Study: 1. Does mental health change with age? Psychol Aging. 1989; 4: 295–306.[CrossRef][Medline] [Order article via Infotrieve]
30. Willett JF. Questions and answers in the measurement of change. In: Rothkopf EZ, ed. Review of Research in Education. Vol. 15. Washington, DC: Am Educational Research Association; 1988: 345–422.
31. Elias MF, Robbins MA, Schultz Jr., NR, Streeten DHP, Elias PK. Clinical significance of cognitive performance by hypertensive patients. Hypertension. 1987; 9: 192–197.
32. Deary IJ, Starr JM, MacLennan WJ. Fluid intelligence, memory and blood pressure in cognitive aging. Personality Individ Diff. 1998; 25: 605–691.[CrossRef]
This article has been cited by other articles:
 |
|
 |
|
  M. F. Elias, M. A. Robbins, M. M. Budge, W. P. Abhayaratna, G. A. Dore, and P. K. Elias Arterial Pulse Wave Velocity and Cognition With Advancing Age Hypertension, April 1, 2009; 53(4): 668 - 673. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. M. Abbatecola, M. Barbieri, M. R. Rizzo, R. Grella, M. T. Laieta, E. Quaranta, A. M. Molinari, M. Cioffi, P. Fioretto, and G. Paolisso Arterial Stiffness and Cognition in Elderly Persons With Impaired Glucose Tolerance and Microalbuminuria J. Gerontol. A Biol. Sci. Med. Sci., September 1, 2008; 63(9): 991 - 996. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Knecht, C. Oelschlager, T. Duning, H. Lohmann, J. Albers, C. Stehling, W. Heindel, G. Breithardt, K. Berger, E. B. Ringelstein, et al. Atrial fibrillation in stroke-free patients is associated with memory impairment and hippocampal atrophy Eur. Heart J., September 1, 2008; 29(17): 2125 - 2132. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. F. Elias, P. K. Elias, G. A. Dore, and M. A. Robbins High-Normal Blood Pressure and Cognition: Supplying the Missing Data Hypertension, July 1, 2008; 52(1): e1 - e2. [Full Text] [PDF]
|
|
|
|
|
|
S. R. Waldstein, S. C. Rice, J. F. Thayer, S. S. Najjar, A. Scuteri, and A. B. Zonderman Pulse Pressure and Pulse Wave Velocity Are Related to Cognitive Decline in the Baltimore Longitudinal Study of Aging Hypertension, January 1, 2008; 51(1): 99 - 104. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. F. Elias, M. A. Robbins, M. M. Budge, P. K. Elias, S. L. Brennan, C. Johnston, Z. Nagy, and C. J. Bates Homocysteine, Folate, and Vitamins B6 and B12 Blood Levels in Relation to Cognitive Performance: The Maine-Syracuse Study Psychosom Med, July 1, 2006; 68(4): 547 - 554. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. A. Robbins, M. F. Elias, P. K. Elias, and M. M. Budge Blood Pressure and Cognitive Function in an African-American and a Caucasian-American Sample: The Maine-Syracuse Study Psychosom Med, September 1, 2005; 67(5): 707 - 714. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Minerva BMJ, November 20, 2004; 329(7476): 1246 - 1246. [Full Text] [PDF]
|
|
|
|
|
|
J. A. Staessen and W. H. Birkenhager Cognitive Impairment and Blood Pressure: Quo Usque Tandem Abutere Patientia Nostra? Hypertension, November 1, 2004; 44(5): 612 - 613. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||