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The relation between cognitive function and UI in healthy, community-dwelling, middle-aged and elderly people
Archives of Gerontology and Geriatrics 53 (2011) 220–224
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Archives of Gerontology and Geriatrics journal homepage: www.elsevier.com/locate/archger
The relation between cognitive function and UI in healthy, community-dwelling, middle-aged and elderly people Takeshi Hatta a,*, Akihiko Iwahara c, Emi Ito b, Taketoshi Hatta d, Nobuyuki Hamajima b a
Deptartment of Health Sciences, Kansai University of Welfare Sciences, 3-11-1, Asahigaoka, Kashiwara City, Osaka 582-0026, Japan Nagoya University, Furoh-cho, Chikusa-ku, Nagoya City, Aichi 464-8601, Japan c Wakayama Medical School, Mikuzu, Wakayama City, Wakayama 641-0011, Japan d Gifu University of Medical Sciences, 795-1, Hiraga-Nagamine, Seki City, Gifu 501-3892, Japan b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 July 2010 Received in revised form 15 November 2010 Accepted 16 November 2010 Available online 15 December 2010
The aim of this study was to examine the relation between UI and cognitive function among nondisabled middle-aged and elderly community-dwelling people. A total of 201 participants (86 men and 115 women) were given a structured questionnaire regarding their condition of UI as well as a cognitive assessment battery (memory, attention, verbal fluency, information processing speed, and visuospatial function). The results showed a significant relation between UI and cognitive tasks for letter fluency, attention, and information processing speed, while no relation was found in cognitive tasks for memory and visuospatial function. Based on these findings, possible mechanisms regarding the relation between UI and cognitive function, and preventive methods to reduce the prevalence of UI in middle-aged and upper middle-aged community dwellers are discussed. ß 2010 Elsevier Ireland Ltd. All rights reserved.
Keywords: Urinary incontinence Letter fluency Memory Attention Prefrontal cortex
1. Introduction UI is one of the cardinal geriatric syndromes, and its prevalence in elderly people increases with advancing age. UI is defined by the International Continence Society (ICS) as a condition in which involuntary loss of urine is a social or hygienic problem and is objectively detectable (Abrams et al., 1988). UI frequently gives rise to discomfort, shame and loss of self-esteem or selfconfidence, which has a strong negative effect on the quality of life (Grimby et al., 1993). It is known that the prevalence of UI increases with age, and that women are more often afflicted than men, due to anatomical reasons. However, the precise mechanisms have not previously been studied (Diokno et al., 1986; Malmstein et al., 1997; Molander et al., 2002). Coppola et al. (2002) reported a relation between UI and cognitive function in elderly people. They assessed the level of UI and cognitive function in elderly people (mean: 74.8 years) who were either in nursing homes or were community-dwellers. They found that the presence of UI was 47.9%, and that there was a sex difference in the type of cases (stress incontinence, urge incontinence, and mixed type). They also reported a significant relation between the prevalence of UI and cognitive decline measured by the mini-mental state examination (MMSE) (Folstein et al., 1975).
* Corresponding author. Tel.: +81 072 947 1379; fax: +81 072 947 1379. E-mail address: [email protected] (T. Hatta). 0167-4943/$ – see front matter ß 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2010.11.020
Several other studies also suggest a significant relation between UI and cognitive decline in community-dwelling elderly persons. For example, Ishizaki et al. (2006) reported the results of an examination between cognitive decline and UI among nondisabled community-dwelling elderly people. Their study consisted of 139 men and 214 women aged from 70 to 94 years whom they designated into the lower and the higher MMSE-score groups and compared their ADLs (daily and instrumental). They found the presence of UI in 9.1% of non-disabled Japanese communitydwellers, suggesting that the cognitive decline (measured by MMSE) was a significant predictor of ADL-decline, while UI was not a predictor of ADL-decline. Huang et al. (2007) examined the relation between cognitive decline, physical function decline, and UI at six-year intervals in older community-dwelling women. The measures used for the study were modified MMSE, Trail B-test and Digit Symbol Substitution-test for cognition, walking speed and time needed to complete five chair stands for physical function. They suggested that both cognitive and physical function declines are important contributors to UI for community-dwelling elderly women, but they failed to find a significant association between cognitive decline and UI. As can be seen from the above mentioned brief reviews, we can conclude first, that the relation between decline of cognitive function and UI is still controversial, probably due to differences in the samples employed and the research methods, and second, that the cognitive examination method used in those studies seems to be tenuous from the standpoint of cognitive neuropsychologists.
T. Hatta et al. / Archives of Gerontology and Geriatrics 53 (2011) 220–224
Therefore, the first purpose of this study was to identify whether non-disabled community-dwelling elderly people show a significant relation between UI and cognitive function decline. Almost all the studies related to UI and cognition employed MMSE as a measure of cognitive function; however, MMSE is actually a general screening test for dementia, though it gives a certain level of information for cognitive function. The MMSE consists of several items such as orientation, attention span and calculation, but the main purpose is to classify whether the participant has dementia or not, rather than to draw a profile of declined cognitive function. It is simply a screening purpose cognitive test. The more recent studies dealing with cognitive decline employ deeper or more structured cognitive test batteries than MMSE, and offer more precise information regarding elderly people, such as specific decline in memory, attention, information processing speed, verbal skill, problem solving, and related abilities. From the above reviewed studies, the characteristics of the relation between UI and cognitive decline are not clear, even if the actual existence of a relation is identified. What type of decline among the different facets of cognitive function (e.g., memory, attention, verbal ability, information processing, visuo-spatial function) relates to UI, or do all facets in fact show similar declining patterns at the onset of UI? The second purpose of this study was to examine the characteristics of the relation between UI and cognitive decline patterns in non-disabled Japanese community dwellers, with a view to seeking any information that might be helpful in finding preventive ways to lessen the prevalence of UI in the elderly. The Nagoya University Cognitive Assessment Battery (NU-CAB), that was developed to assess cognitive function of community dwellers, was employed in this study to draw a profile of declining cognitive function. 2. Subjects and methods 2.1. Participants Two hundred and one participants who participated in 2006 Nagoya University Y-town cohort study (n = 888) were enrolled in this study. They were selected according to the following criteria; those who answered the questionnaire without voluntarily missing any questions, who were given NU-CAB and a thorough clinical examination. Participants in this study showed no sign of any serious frailty syndrome such as metastasized neoplastic disease, psychiatric illness or sign of dementia. Informed consent was obtained from participants, and the study was approved by the Ethical Committee of Nagoya University Medical School. Participants, whose MMSE scores were below 26 as calculated by NUCAB, were deleted from the analysis of data. The basic characteristic of participants is shown in Table 1. 2.2. Measures UI was measured based on the response to items in a questionnaire that was part of a booklet that consisted of daily life customs, physical condition, psychosocial issues, etc. The
Table 1 Basic characteristics of participants in this study (n = 201). Mean age (years) Age range (years) Age class (% >80) Gender (% women) Education status, mean (years) Education status range (years) Presence of UI (%)
61.45 40–88 3.98 57.21 10.55 8–16 25.34
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responses addressed in this study were those to questions such as ‘‘the question might not be easy to talk about, but it is very important for the research of the Y-Town health examination. During the last 12 months, have you lost any amount of urine beyond your control?’’ If subjects responded ‘yes’ to this question they were then asked for details concerning the frequency and type of incontinence (urge or stress). As the present analysis was a preliminary one, we classified the participants into two groups, UI and Intact. The UI group consisted of participants who reported UI experience irrespective of the frequency or type, while the Intact group participants had no experience of UI at all. 2.3. Cognitive assessment The NU-CAB was employed to assess participants’ cognitive abilities as a part of medical examination. The NU-CAB addressed mainly the assessment of individual frontal cortex related abilities such as attention, language, memory, working memory and executive functions (Hatta, 2003). The reliability and validity have been examined and reported elsewhere (Hatta, 2004; Hatta et al., 2005; Ito and Hatta, 2006). This neuropsychological test battery consisted of several test items such as word recall test (WRT), logical memory test (LMT) (Japanese short version of Wechsler memory scale), digit cancelation test (D-CAT), money road test (MRT), Stroop test (Stroop, 1935), verbal fluency test (VFT), letter fluency test (LFT) and semantic fluency test (SFT). Among these NU-CAB items, we used the following 5 items (7 indices) to address the aim of our present research. Precise procedures of each test item addressed in this study were as follows. The test was given individually according to the time required by the participants. In the LMT, the examiner read a short story, consisting of 25 segments, twice, and each participant was asked to recall the story immediately. Usually the LMT takes into consideration both immediate and delayed conditions, but in our medical checkup only immediate recall was considered, since previous examination of the correlation coefficient between the scores of immediate and delayed recall conditions was sufficiently high (r = 0.92) (Hatta et al., 2005). Each segment that was correctly recalled by the participant was assigned a score of 1 point, therefore the total score ranged from 0 to 25 points. This method was employed to examine the memory function. In the Stroop test, participants were asked to name the color of the words ‘red’, ‘blue’, ‘yellow’, ‘green’ as fast and accurately as possible, although the words were printed in colors that differed from the name. The participants were also asked to name the color of a patch. The Stroop stimuli and color patch consisted of 40 words, and the response time and errors in the names were measured by the examiner. Required time (in seconds) to complete color patch naming was used as the index of Stroop-dot condition. The required time (in seconds) to name Stroop stimuli was the index of Stroop condition, and the index of Stroop score was calculated by the formula: ((RT in the Stoop condition) (RT in the dot condition)) (((RT in the Stroop condition) + (RT in the dot condition))) 100. As the error rate was too low to regard as a variable, we used only required time scores in the analyses. The index of the Stroopdot condition was regarded as a reflection of information processing speed and focusing attention. According to the study by MacLeod and MacDonald (2000), the indices of Stroop condition and Stroop score were employed to assess focusing attention and executive function of working memory theory. The index of D-CAT (hit 3) was used to assess information processing speed, focusing attention and sustained attention concentration that relate to an executive function of working memory theory. The D-CAT developed by Hatta et al. (2001) is a
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Table 2 Mean S.D scores in the cognitive tests as a function of sex. UI group
Number of participants LMT Stroop dot condition Stroop condition Stroop score D-CAT 3 targets LFT MRT
Controls
Men
Women
Men
Women
19 11.68 6.33 39.68 18.34 53.63 20.42 15.40 8.93 37.16 10.77 16.63 5.35 10.26 2.42
32 14.22 5.70 30.09 6.48 43.31 18.31 16.36 10.46 42.19 10.07 21.81 6.42 9.13 2.08
67 12.37 5.68 32.51 8.62 48.07 16.58 17.94 11.83 40.12 12.29 20.10 8.51 10.25 2.33
83 4.40 5.13 1.28 9.75 46.25 20.1 16.78 12.4 46.00 13.7 22.84 8.43 8.92 2.59
paper and pencil type of screening test for attention, and it basically follows Sohlberg and Matter’s (1989) attention model, in which they proposed five hierarchical classifications; each component of the hierarchy requiring the effective functioning of the one below it. The D-CAT aimed to evaluate three levels of attention, focused attention, sustained attention concentration and selective attention. Since the revised version of the D-CAT norm (Hatta et al., 2006) is published every 10 years for men and women from the age of 18 to the age of 89, based upon more than 2000 samples, it has become widely used in Japan (for example, the D-CAT was nominated as one of the attention tests for the official evaluation of the difficulties in traumatic brain injury = TBI patients). The test sheet of the D-CAT consisted of 12 rows of 50 digits. Each row contained 5 sets of the numbers 0–9 arranged in random order. In the index of D-CAT (hit 3), participants were instructed to search for the target numbers (8, 3 and 7) and to delete each one with a slash mark as fast and as accurately as possible until the experimenter sent a stop signal. The experimenter stressed that all of the target numbers should be canceled without omission. The LFT was used to examine language and executive function. In this task, a Japanese letter, either ‘‘a’’ or ‘‘ka’’, was given to each participant, who was asked to generate common nouns beginning with this letter—as many as possible in 60 s. The participants were instructed not to include proper nouns or to repeat one that had already been mentioned. The score in each task was based on the number of words reported. The reliability and validity of Japanese LFT were demonstrated by Ito et al. (2004), and Ito and Hatta (2006). In the MRT, developed by Butters et al. (1972), a visuo-spatial function was assessed. The test used was a shortened version consisting of 2 cm wide road figures with 12 turns of various angles. After two practice trials using road figures with 4 turns, a test trial was administered. The participants were asked whether the turn should be to the right or the left at each turning point on the drawn road picture. They had to do this task without any head or body movements, but only mental rotation. The score assigned was 1 point for a correct answer at each turn, therefore the total score ranged from 0 to 12 points.
The results of ANCOVA for the LMT showed a significant sex difference (F1,195 = 6.17, p < 0.01; women advantage) but no group difference (F1,195 = 0.20) or interaction between sex and group (F1,195 = 0.21). As for the results of the MRT, the main factor of sex was significant (F1,195 = 11.84, p < 0.01, male advantage); however, both the group and the interaction were non-significant (F1,195 = 0.12 and 0.13, respectively). The verbal memory advantage, like the spatial ability advantage, for men over women is consistent with a well-known sex difference pattern in cognitive function (e.g., Kimura, 1999). The results of the Stroop condition showed a significant interaction between sex and group (F1,195 = 3.83, p < 0.05), reflecting the fact that while the sex factor showed a tendency of advantage in women, no difference was shown in the group factor (F1,195 = 3.32, p < 0.07, and F1,195 = 0.05). These results suggest that the performance of UI men was poorer (slow RTs) than that of the control group, whereas both women UI and control groups showed a similar level of performance. The results of the Stroop dot condition showed a significant difference for both sex and group (F1,195 = 10.46 and 3.86, p < 0.01 and 0.05, respectively), and the interaction was also significant (F1,195 = 10.19, p < 0.01). The profile of both indices is similar. Fig. 1 of the Stroop condition shows the pattern results which suggest that the control group of both sexes showed a similar level of performance, whereas the group of UI men showed a poorer performance (slow RTs) than that of the control men’s group. The Stroop score results did not show any significant difference in sex (F1,195 = 0.01), group (F1,195 = 0.65) or the interaction (F1,195 = 0.22). The ANCOVA for the LFT showed a significant difference in sex (F1,195 = 9.56, p < 0.01) and group (F1,195 = 3.02, p <0.05) difference, but did not show an interaction (F1,195 = 1.24). These results suggest a better performance in women than in men and a better performance of the control than the UI group.
3. Results Table 2 shows mean S.D. scores of each index of cognitive function as a function of group and sex. As a sex difference in UI prevalence had been reported in previous studies, as well as cognitive function correlated with age and history of education (Bosma et al., 2003), and since our primary concern was to identify the relations between UI and states of cognitive function, an analysis of covariance (ANCOVA) was administered to each index, where sex and group (UI/ control) were independent variables, and age and history of education were regarded as control variables.
Fig. 1. Mean performance of UI and control group participants as a function of sex in the Stroop dot condition. The vertical axis indicates the required time to complete task (s).
T. Hatta et al. / Archives of Gerontology and Geriatrics 53 (2011) 220–224
Fig. 2. Mean performance of UI and control group participants as a function of sex in the D-CAT (hit 3). The vertical axis indicates the number of digits correctly marked.
Finally, the results for the D-CAT (hit 3) showed a significant sex difference (F1,195 = 6.72, p < 0.01) and group difference (F1,195 = 3.52, p < 0.05) but no interaction (F1,195 = 0.01). These results of LFT and D-CAT (hit 3) are similar, and suggest a better performance in women than in men, as well as a better performance of the control than of the UI group. Fig. 2 shows the D-CAT (hit 3) results as representative, and it offers a clear profile understanding. To sum up, these analyses showed first, that a significant sex difference was shown for all indices except for the index of the Stroop score; second, that the indices revealed poorer performances in the UI than in the control group except for the LMT and the MRT; and third, that the two indices (Stroop dot condition and Stroop condition) showed the interaction between cognitive performance and sex, where the UI male group was poorer than the control group while the female group showed no group difference (UI and control). Finally, two indices (D-CAT (hit 3) and LFT) showed a poorer performance in the UI than in the control in both men and women. Putting together, there was, as we expected, a robust specific relation between cognitive performance and UI. 4. Discussion First, the prevalence of UI among our sample of non-disabled community-dwellers over the age of 40 showed a sex difference; namely, that it was more prevalent in women (27%) than in men (22%). This tendency coincides with the findings of HolyroydLeduc et al. (2004) where UI prevalence was 18.5% in women and 8.5% in men, and of Molander et al. (2002), where UI prevalence was 48% among women compared with 17% in men. Coppola et al. (2002) reported no sex difference in the prevalence of UI, 51% in men and 45.8% in women. Ishizaki et al. (2006) reported that UI prevalence among non-disabled Japanese community- dwellers over 70 years of age was 9.3%, but gave no information as to sex difference. Compared to their findings, our prevalence rate in Japanese non-disabled community-dwellers seems to be somewhat high. The reason for this difference is not clear but it might possibly reflect the difference in examination procedures and definition of UI. Our primary concern in this study was not to discuss the UI prevalence rate but rather to examine the relations between UI and cognitive functions more systematically than that of related previous studies described earlier. This study was based on two premises. The first was that all previous studies that examined the relation between UI and cognitive function employed MMSE for evaluation of participants’ cognitive ability. Information based on MMSE seems feeble from the standpoint of recent cognitive psychological research and does not offer a specified profile of
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cognitive decline. The second premise relates to the validity of MMSE, since another study claimed that MMSE could not be regarded as a reliable screening test for frontal lobe dysfunction (Iwahara et al., 2006). The latter authors found that a substantial number of people whose score of MMSE was over 23 points (e.g., 60% in LMT and 83% in Stroop test) showed a poor performance of less than 2 S.D. from the mean in each item of the cognitive test battery (NU-CAB). Moreover, their participants (n = 336) ranged in age from 39 to 86 years, which implies that MMSE is not necessarily a valuable test for examination of cognitive function in elderly people. In this study we employed NU-CAB rather than MMSE to examine the relations between UI and cognitive function. The NUCAB was developed to assess cognitive abilities as a part of a medical check-up in the Nagoya University Y-Town cohort study, and addressed examinations pertaining to attention, language, memory, working memory and executive functions (Hatta, 2003). The reliability and validity were examined and reported elsewhere (Hatta, 2004; Hatta et al., 2005; Ito and Hatta, 2006). For example, the validity examination by means of the NIRS (Near-InfraRed Spectroscopy) identified robust activation of prefrontal cortex in the LFT, and temporal plus frontal cortex activation in the SFT and the LMT (Hatta et al., 2009). Among the NU-CAB items, we used 7 indices to address our present research objectives. Regarding cognitive mechanisms for the Stroop test, MacLeod and MacDonald (2000) and Mead et al. (2002) suggested a strong engagement of the frontal cortex in the Stroop condition that requires attention retention and response inhibition. As for the MRT, strong engagement of the right hemisphere frontal and temporal areas are suggested (Ito et al., 2004; Ito and Hatta, 2006; Hatta et al., 2008). The main findings for the relations between UI and cognitive indices in this study can be summarized as follows. First, both indices for memory (LMT) and visual-spatial ability (MRT) did not show a group difference between UI and control. Second, the index addressed information processing speed (Stroop test) and showed a partial interaction between group and sex of participants. Finally, both indices for verbal ability (LFT) and information processing speed (D-CAT, hit 3) showed a group difference where poorer performance was shown in UI than in the control group irrespective of their sex. Figs. 1 and 2 show different types of results and induce a better understanding. According to our hypothetical correspondence between the index used and brain function, these findings suggest that brain function mainly reflects the role of the prefrontal area (e.g., LFT and D-CAT (hit 3)) and strongly relates to UI incidence, whereas the corresponding brain function temporal area (e.g., LMT and MRT) does not show a significant relation to UI. The partial interaction shown between group and sex in the indices of Stroop dot and Stroop condition does not necessarily contradict this summary, since a poorer performance in UI than control was shown in men, though in women the difference did not reach a significant level. According to the textbook, anatomical bases of lower urinary tract neural mechanisms are as follows: there are three kinds of nerves (pelvic, hypogastric and pudendal) in the urinary bladder, of which the hypogastric nerve and the pudendal nerve control the sphincter of urinary bladder. Urinary intention is mediated by the pelvic and the hypogastric nerves. These peripheral nerves are controlled by the urination center of the brain stem. The function of the urination center at the brain stem is under the control of the frontal lobe of the brain. In short, the function of the external urethral sphincter (voluntary muscle) that is under the control of the frontal lobe of the brain relates strongly to UI. These neural bases of excretion mechanisms generate a hypothesis that the frontal lobe function in the UI group must
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be inferior to that of the control group, because UI is caused by any acquired dysfunction of the frontal cortex in middle- and upper middle-aged people. Therefore, cognitive test performance of frontal lobe in UI must be inferior to that of the control group, whereas cognitive performances that related to the other area (e.g., temporal area) do not show a group difference. Our findings seem to correspond with our hypothesis, namely that prefrontal cortex related index, such as LFT and D-CAT (hit 3), showed a significant group difference between the UI and the control group; that is, the performance of UI was significantly inferior to that of the control. Using a new brain imaging technique, NIRS, Hatta et al. (2008, 2009) confirmed robust prefrontal cortex activation in LFT and D-CAT (hit 3) indices. On the other hand, temporal area related indices such as LMT and MRT showed no difference between UI and control groups. Stroop test performance showed rather complicated results, although not inconsistent with our hypothesis. In short, our present findings indicate an important role of prefrontal cortex on the incidence of UI in the middle and upper middle non-disabled elderly. This indication recalls the study by Inzitari et al. (2008) where they examined whether subtle, but clinically detectable, neurological abnormalities (SNAs) are associated with lower cognitive and physical performance in elderly persons (the mean age was 71.9 years). They found that SNAs have a prospective association with cognitive and physical performance decline in older community-dwelling persons. Compared with low SNA score people, higher SNA score people have an increased risk of cognitive dysfunction and death. These studies, along with the present findings, generate an intuitive flow-chart of a negative spiral, that subtle neurological abnormality (e.g., UI) reflects a decline of cognitive performance and self-esteem, which brings about hesitation in anti-human communication situations, followed by a tendency to stay at home, thus bringing about a further decline of cognitive function in elderly people and precipitating causes of UI. If we combine the idea of SNAs by Inzitari et al. (2008) with our findings, we may be able to regard the UI incidence as a sign for SNA. As our findings, as already may be seen, show a strong relation between UI and cognitive tasks decline (LFT and D-CAT (hit 3)) that reflects prefrontal cortex function, we may be able to consider ways to curb the incidence of UI, or to correct precipitating processes by introducing some cognitive training to activate prefrontal cortex. If we develop a program to sustain cognitive function corresponding with prefrontal area from early middle age of intact people, the incidence of UI could be retarded. The retardation of UI incidence would give rise to positive self-esteem among middle-aged people, and expand inter-human communication, and thus create a positive spiral. This positive spiral must surely be a preventive activity to lessen UI prevalence. If we further expand these ideas, this may begin to play some role in relieving the psychosocial and economical burden of UI in elderly populations (Herzog et al., 1989; Ekelund et al., 1993; DuBeau et al., 1998; Wagner and Hu, 1998). Conflict of interest statement None. Acknowledgements This study was the part of Yakumo study and has been supported by the Grant-in-Aid for sicentific research (B) to the first author (#19330158). Authors expressed great appreciation to the support of staff members engaged with Yakumo Study of Yakumo Town and all participants.
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Neural basis of the Stroop interference task: response competition or selective attention. J. Int. Neuropsychol. Soc. 8, 735–742. Molander, U., Sundh, V., Steen, B., 2002. Urinary incontinence and related symptom infolder men and women studies longitudinally between 70 and 97 years of age. A population study. Arch. Gerontol. Geriatr. 35, 237–244. Sohlberg, M.M., Matter, C.A., 1989. Introduction to Cognitive Rehabilitation: Theory and Practice. Oxford University Press, New York. Stroop, J.R., 1935. Studies of interference in serial verbal reactions. J. Exp. Psychol. 18, 643–662. Wagner, T.H., Hu, T.W., 1998. Economic costs of urinary inconsistence in 1995. Urology 51, 355–361.
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The relation between cognitive function and UI in healthy, community-dwelling, middle-aged and elderly people Takeshi Hatta a,*, Akihiko Iwahara c, Emi Ito b, Taketoshi Hatta d, Nobuyuki Hamajima b a
Deptartment of Health Sciences, Kansai University of Welfare Sciences, 3-11-1, Asahigaoka, Kashiwara City, Osaka 582-0026, Japan Nagoya University, Furoh-cho, Chikusa-ku, Nagoya City, Aichi 464-8601, Japan c Wakayama Medical School, Mikuzu, Wakayama City, Wakayama 641-0011, Japan d Gifu University of Medical Sciences, 795-1, Hiraga-Nagamine, Seki City, Gifu 501-3892, Japan b
A R T I C L E I N F O
A B S T R A C T
Article history: Received 30 July 2010 Received in revised form 15 November 2010 Accepted 16 November 2010 Available online 15 December 2010
The aim of this study was to examine the relation between UI and cognitive function among nondisabled middle-aged and elderly community-dwelling people. A total of 201 participants (86 men and 115 women) were given a structured questionnaire regarding their condition of UI as well as a cognitive assessment battery (memory, attention, verbal fluency, information processing speed, and visuospatial function). The results showed a significant relation between UI and cognitive tasks for letter fluency, attention, and information processing speed, while no relation was found in cognitive tasks for memory and visuospatial function. Based on these findings, possible mechanisms regarding the relation between UI and cognitive function, and preventive methods to reduce the prevalence of UI in middle-aged and upper middle-aged community dwellers are discussed. ß 2010 Elsevier Ireland Ltd. All rights reserved.
Keywords: Urinary incontinence Letter fluency Memory Attention Prefrontal cortex
1. Introduction UI is one of the cardinal geriatric syndromes, and its prevalence in elderly people increases with advancing age. UI is defined by the International Continence Society (ICS) as a condition in which involuntary loss of urine is a social or hygienic problem and is objectively detectable (Abrams et al., 1988). UI frequently gives rise to discomfort, shame and loss of self-esteem or selfconfidence, which has a strong negative effect on the quality of life (Grimby et al., 1993). It is known that the prevalence of UI increases with age, and that women are more often afflicted than men, due to anatomical reasons. However, the precise mechanisms have not previously been studied (Diokno et al., 1986; Malmstein et al., 1997; Molander et al., 2002). Coppola et al. (2002) reported a relation between UI and cognitive function in elderly people. They assessed the level of UI and cognitive function in elderly people (mean: 74.8 years) who were either in nursing homes or were community-dwellers. They found that the presence of UI was 47.9%, and that there was a sex difference in the type of cases (stress incontinence, urge incontinence, and mixed type). They also reported a significant relation between the prevalence of UI and cognitive decline measured by the mini-mental state examination (MMSE) (Folstein et al., 1975).
* Corresponding author. Tel.: +81 072 947 1379; fax: +81 072 947 1379. E-mail address: [email protected] (T. Hatta). 0167-4943/$ – see front matter ß 2010 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.archger.2010.11.020
Several other studies also suggest a significant relation between UI and cognitive decline in community-dwelling elderly persons. For example, Ishizaki et al. (2006) reported the results of an examination between cognitive decline and UI among nondisabled community-dwelling elderly people. Their study consisted of 139 men and 214 women aged from 70 to 94 years whom they designated into the lower and the higher MMSE-score groups and compared their ADLs (daily and instrumental). They found the presence of UI in 9.1% of non-disabled Japanese communitydwellers, suggesting that the cognitive decline (measured by MMSE) was a significant predictor of ADL-decline, while UI was not a predictor of ADL-decline. Huang et al. (2007) examined the relation between cognitive decline, physical function decline, and UI at six-year intervals in older community-dwelling women. The measures used for the study were modified MMSE, Trail B-test and Digit Symbol Substitution-test for cognition, walking speed and time needed to complete five chair stands for physical function. They suggested that both cognitive and physical function declines are important contributors to UI for community-dwelling elderly women, but they failed to find a significant association between cognitive decline and UI. As can be seen from the above mentioned brief reviews, we can conclude first, that the relation between decline of cognitive function and UI is still controversial, probably due to differences in the samples employed and the research methods, and second, that the cognitive examination method used in those studies seems to be tenuous from the standpoint of cognitive neuropsychologists.
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Therefore, the first purpose of this study was to identify whether non-disabled community-dwelling elderly people show a significant relation between UI and cognitive function decline. Almost all the studies related to UI and cognition employed MMSE as a measure of cognitive function; however, MMSE is actually a general screening test for dementia, though it gives a certain level of information for cognitive function. The MMSE consists of several items such as orientation, attention span and calculation, but the main purpose is to classify whether the participant has dementia or not, rather than to draw a profile of declined cognitive function. It is simply a screening purpose cognitive test. The more recent studies dealing with cognitive decline employ deeper or more structured cognitive test batteries than MMSE, and offer more precise information regarding elderly people, such as specific decline in memory, attention, information processing speed, verbal skill, problem solving, and related abilities. From the above reviewed studies, the characteristics of the relation between UI and cognitive decline are not clear, even if the actual existence of a relation is identified. What type of decline among the different facets of cognitive function (e.g., memory, attention, verbal ability, information processing, visuo-spatial function) relates to UI, or do all facets in fact show similar declining patterns at the onset of UI? The second purpose of this study was to examine the characteristics of the relation between UI and cognitive decline patterns in non-disabled Japanese community dwellers, with a view to seeking any information that might be helpful in finding preventive ways to lessen the prevalence of UI in the elderly. The Nagoya University Cognitive Assessment Battery (NU-CAB), that was developed to assess cognitive function of community dwellers, was employed in this study to draw a profile of declining cognitive function. 2. Subjects and methods 2.1. Participants Two hundred and one participants who participated in 2006 Nagoya University Y-town cohort study (n = 888) were enrolled in this study. They were selected according to the following criteria; those who answered the questionnaire without voluntarily missing any questions, who were given NU-CAB and a thorough clinical examination. Participants in this study showed no sign of any serious frailty syndrome such as metastasized neoplastic disease, psychiatric illness or sign of dementia. Informed consent was obtained from participants, and the study was approved by the Ethical Committee of Nagoya University Medical School. Participants, whose MMSE scores were below 26 as calculated by NUCAB, were deleted from the analysis of data. The basic characteristic of participants is shown in Table 1. 2.2. Measures UI was measured based on the response to items in a questionnaire that was part of a booklet that consisted of daily life customs, physical condition, psychosocial issues, etc. The
Table 1 Basic characteristics of participants in this study (n = 201). Mean age (years) Age range (years) Age class (% >80) Gender (% women) Education status, mean (years) Education status range (years) Presence of UI (%)
61.45 40–88 3.98 57.21 10.55 8–16 25.34
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responses addressed in this study were those to questions such as ‘‘the question might not be easy to talk about, but it is very important for the research of the Y-Town health examination. During the last 12 months, have you lost any amount of urine beyond your control?’’ If subjects responded ‘yes’ to this question they were then asked for details concerning the frequency and type of incontinence (urge or stress). As the present analysis was a preliminary one, we classified the participants into two groups, UI and Intact. The UI group consisted of participants who reported UI experience irrespective of the frequency or type, while the Intact group participants had no experience of UI at all. 2.3. Cognitive assessment The NU-CAB was employed to assess participants’ cognitive abilities as a part of medical examination. The NU-CAB addressed mainly the assessment of individual frontal cortex related abilities such as attention, language, memory, working memory and executive functions (Hatta, 2003). The reliability and validity have been examined and reported elsewhere (Hatta, 2004; Hatta et al., 2005; Ito and Hatta, 2006). This neuropsychological test battery consisted of several test items such as word recall test (WRT), logical memory test (LMT) (Japanese short version of Wechsler memory scale), digit cancelation test (D-CAT), money road test (MRT), Stroop test (Stroop, 1935), verbal fluency test (VFT), letter fluency test (LFT) and semantic fluency test (SFT). Among these NU-CAB items, we used the following 5 items (7 indices) to address the aim of our present research. Precise procedures of each test item addressed in this study were as follows. The test was given individually according to the time required by the participants. In the LMT, the examiner read a short story, consisting of 25 segments, twice, and each participant was asked to recall the story immediately. Usually the LMT takes into consideration both immediate and delayed conditions, but in our medical checkup only immediate recall was considered, since previous examination of the correlation coefficient between the scores of immediate and delayed recall conditions was sufficiently high (r = 0.92) (Hatta et al., 2005). Each segment that was correctly recalled by the participant was assigned a score of 1 point, therefore the total score ranged from 0 to 25 points. This method was employed to examine the memory function. In the Stroop test, participants were asked to name the color of the words ‘red’, ‘blue’, ‘yellow’, ‘green’ as fast and accurately as possible, although the words were printed in colors that differed from the name. The participants were also asked to name the color of a patch. The Stroop stimuli and color patch consisted of 40 words, and the response time and errors in the names were measured by the examiner. Required time (in seconds) to complete color patch naming was used as the index of Stroop-dot condition. The required time (in seconds) to name Stroop stimuli was the index of Stroop condition, and the index of Stroop score was calculated by the formula: ((RT in the Stoop condition) (RT in the dot condition)) (((RT in the Stroop condition) + (RT in the dot condition))) 100. As the error rate was too low to regard as a variable, we used only required time scores in the analyses. The index of the Stroopdot condition was regarded as a reflection of information processing speed and focusing attention. According to the study by MacLeod and MacDonald (2000), the indices of Stroop condition and Stroop score were employed to assess focusing attention and executive function of working memory theory. The index of D-CAT (hit 3) was used to assess information processing speed, focusing attention and sustained attention concentration that relate to an executive function of working memory theory. The D-CAT developed by Hatta et al. (2001) is a
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Table 2 Mean S.D scores in the cognitive tests as a function of sex. UI group
Number of participants LMT Stroop dot condition Stroop condition Stroop score D-CAT 3 targets LFT MRT
Controls
Men
Women
Men
Women
19 11.68 6.33 39.68 18.34 53.63 20.42 15.40 8.93 37.16 10.77 16.63 5.35 10.26 2.42
32 14.22 5.70 30.09 6.48 43.31 18.31 16.36 10.46 42.19 10.07 21.81 6.42 9.13 2.08
67 12.37 5.68 32.51 8.62 48.07 16.58 17.94 11.83 40.12 12.29 20.10 8.51 10.25 2.33
83 4.40 5.13 1.28 9.75 46.25 20.1 16.78 12.4 46.00 13.7 22.84 8.43 8.92 2.59
paper and pencil type of screening test for attention, and it basically follows Sohlberg and Matter’s (1989) attention model, in which they proposed five hierarchical classifications; each component of the hierarchy requiring the effective functioning of the one below it. The D-CAT aimed to evaluate three levels of attention, focused attention, sustained attention concentration and selective attention. Since the revised version of the D-CAT norm (Hatta et al., 2006) is published every 10 years for men and women from the age of 18 to the age of 89, based upon more than 2000 samples, it has become widely used in Japan (for example, the D-CAT was nominated as one of the attention tests for the official evaluation of the difficulties in traumatic brain injury = TBI patients). The test sheet of the D-CAT consisted of 12 rows of 50 digits. Each row contained 5 sets of the numbers 0–9 arranged in random order. In the index of D-CAT (hit 3), participants were instructed to search for the target numbers (8, 3 and 7) and to delete each one with a slash mark as fast and as accurately as possible until the experimenter sent a stop signal. The experimenter stressed that all of the target numbers should be canceled without omission. The LFT was used to examine language and executive function. In this task, a Japanese letter, either ‘‘a’’ or ‘‘ka’’, was given to each participant, who was asked to generate common nouns beginning with this letter—as many as possible in 60 s. The participants were instructed not to include proper nouns or to repeat one that had already been mentioned. The score in each task was based on the number of words reported. The reliability and validity of Japanese LFT were demonstrated by Ito et al. (2004), and Ito and Hatta (2006). In the MRT, developed by Butters et al. (1972), a visuo-spatial function was assessed. The test used was a shortened version consisting of 2 cm wide road figures with 12 turns of various angles. After two practice trials using road figures with 4 turns, a test trial was administered. The participants were asked whether the turn should be to the right or the left at each turning point on the drawn road picture. They had to do this task without any head or body movements, but only mental rotation. The score assigned was 1 point for a correct answer at each turn, therefore the total score ranged from 0 to 12 points.
The results of ANCOVA for the LMT showed a significant sex difference (F1,195 = 6.17, p < 0.01; women advantage) but no group difference (F1,195 = 0.20) or interaction between sex and group (F1,195 = 0.21). As for the results of the MRT, the main factor of sex was significant (F1,195 = 11.84, p < 0.01, male advantage); however, both the group and the interaction were non-significant (F1,195 = 0.12 and 0.13, respectively). The verbal memory advantage, like the spatial ability advantage, for men over women is consistent with a well-known sex difference pattern in cognitive function (e.g., Kimura, 1999). The results of the Stroop condition showed a significant interaction between sex and group (F1,195 = 3.83, p < 0.05), reflecting the fact that while the sex factor showed a tendency of advantage in women, no difference was shown in the group factor (F1,195 = 3.32, p < 0.07, and F1,195 = 0.05). These results suggest that the performance of UI men was poorer (slow RTs) than that of the control group, whereas both women UI and control groups showed a similar level of performance. The results of the Stroop dot condition showed a significant difference for both sex and group (F1,195 = 10.46 and 3.86, p < 0.01 and 0.05, respectively), and the interaction was also significant (F1,195 = 10.19, p < 0.01). The profile of both indices is similar. Fig. 1 of the Stroop condition shows the pattern results which suggest that the control group of both sexes showed a similar level of performance, whereas the group of UI men showed a poorer performance (slow RTs) than that of the control men’s group. The Stroop score results did not show any significant difference in sex (F1,195 = 0.01), group (F1,195 = 0.65) or the interaction (F1,195 = 0.22). The ANCOVA for the LFT showed a significant difference in sex (F1,195 = 9.56, p < 0.01) and group (F1,195 = 3.02, p <0.05) difference, but did not show an interaction (F1,195 = 1.24). These results suggest a better performance in women than in men and a better performance of the control than the UI group.
3. Results Table 2 shows mean S.D. scores of each index of cognitive function as a function of group and sex. As a sex difference in UI prevalence had been reported in previous studies, as well as cognitive function correlated with age and history of education (Bosma et al., 2003), and since our primary concern was to identify the relations between UI and states of cognitive function, an analysis of covariance (ANCOVA) was administered to each index, where sex and group (UI/ control) were independent variables, and age and history of education were regarded as control variables.
Fig. 1. Mean performance of UI and control group participants as a function of sex in the Stroop dot condition. The vertical axis indicates the required time to complete task (s).
T. Hatta et al. / Archives of Gerontology and Geriatrics 53 (2011) 220–224
Fig. 2. Mean performance of UI and control group participants as a function of sex in the D-CAT (hit 3). The vertical axis indicates the number of digits correctly marked.
Finally, the results for the D-CAT (hit 3) showed a significant sex difference (F1,195 = 6.72, p < 0.01) and group difference (F1,195 = 3.52, p < 0.05) but no interaction (F1,195 = 0.01). These results of LFT and D-CAT (hit 3) are similar, and suggest a better performance in women than in men, as well as a better performance of the control than of the UI group. Fig. 2 shows the D-CAT (hit 3) results as representative, and it offers a clear profile understanding. To sum up, these analyses showed first, that a significant sex difference was shown for all indices except for the index of the Stroop score; second, that the indices revealed poorer performances in the UI than in the control group except for the LMT and the MRT; and third, that the two indices (Stroop dot condition and Stroop condition) showed the interaction between cognitive performance and sex, where the UI male group was poorer than the control group while the female group showed no group difference (UI and control). Finally, two indices (D-CAT (hit 3) and LFT) showed a poorer performance in the UI than in the control in both men and women. Putting together, there was, as we expected, a robust specific relation between cognitive performance and UI. 4. Discussion First, the prevalence of UI among our sample of non-disabled community-dwellers over the age of 40 showed a sex difference; namely, that it was more prevalent in women (27%) than in men (22%). This tendency coincides with the findings of HolyroydLeduc et al. (2004) where UI prevalence was 18.5% in women and 8.5% in men, and of Molander et al. (2002), where UI prevalence was 48% among women compared with 17% in men. Coppola et al. (2002) reported no sex difference in the prevalence of UI, 51% in men and 45.8% in women. Ishizaki et al. (2006) reported that UI prevalence among non-disabled Japanese community- dwellers over 70 years of age was 9.3%, but gave no information as to sex difference. Compared to their findings, our prevalence rate in Japanese non-disabled community-dwellers seems to be somewhat high. The reason for this difference is not clear but it might possibly reflect the difference in examination procedures and definition of UI. Our primary concern in this study was not to discuss the UI prevalence rate but rather to examine the relations between UI and cognitive functions more systematically than that of related previous studies described earlier. This study was based on two premises. The first was that all previous studies that examined the relation between UI and cognitive function employed MMSE for evaluation of participants’ cognitive ability. Information based on MMSE seems feeble from the standpoint of recent cognitive psychological research and does not offer a specified profile of
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cognitive decline. The second premise relates to the validity of MMSE, since another study claimed that MMSE could not be regarded as a reliable screening test for frontal lobe dysfunction (Iwahara et al., 2006). The latter authors found that a substantial number of people whose score of MMSE was over 23 points (e.g., 60% in LMT and 83% in Stroop test) showed a poor performance of less than 2 S.D. from the mean in each item of the cognitive test battery (NU-CAB). Moreover, their participants (n = 336) ranged in age from 39 to 86 years, which implies that MMSE is not necessarily a valuable test for examination of cognitive function in elderly people. In this study we employed NU-CAB rather than MMSE to examine the relations between UI and cognitive function. The NUCAB was developed to assess cognitive abilities as a part of a medical check-up in the Nagoya University Y-Town cohort study, and addressed examinations pertaining to attention, language, memory, working memory and executive functions (Hatta, 2003). The reliability and validity were examined and reported elsewhere (Hatta, 2004; Hatta et al., 2005; Ito and Hatta, 2006). For example, the validity examination by means of the NIRS (Near-InfraRed Spectroscopy) identified robust activation of prefrontal cortex in the LFT, and temporal plus frontal cortex activation in the SFT and the LMT (Hatta et al., 2009). Among the NU-CAB items, we used 7 indices to address our present research objectives. Regarding cognitive mechanisms for the Stroop test, MacLeod and MacDonald (2000) and Mead et al. (2002) suggested a strong engagement of the frontal cortex in the Stroop condition that requires attention retention and response inhibition. As for the MRT, strong engagement of the right hemisphere frontal and temporal areas are suggested (Ito et al., 2004; Ito and Hatta, 2006; Hatta et al., 2008). The main findings for the relations between UI and cognitive indices in this study can be summarized as follows. First, both indices for memory (LMT) and visual-spatial ability (MRT) did not show a group difference between UI and control. Second, the index addressed information processing speed (Stroop test) and showed a partial interaction between group and sex of participants. Finally, both indices for verbal ability (LFT) and information processing speed (D-CAT, hit 3) showed a group difference where poorer performance was shown in UI than in the control group irrespective of their sex. Figs. 1 and 2 show different types of results and induce a better understanding. According to our hypothetical correspondence between the index used and brain function, these findings suggest that brain function mainly reflects the role of the prefrontal area (e.g., LFT and D-CAT (hit 3)) and strongly relates to UI incidence, whereas the corresponding brain function temporal area (e.g., LMT and MRT) does not show a significant relation to UI. The partial interaction shown between group and sex in the indices of Stroop dot and Stroop condition does not necessarily contradict this summary, since a poorer performance in UI than control was shown in men, though in women the difference did not reach a significant level. According to the textbook, anatomical bases of lower urinary tract neural mechanisms are as follows: there are three kinds of nerves (pelvic, hypogastric and pudendal) in the urinary bladder, of which the hypogastric nerve and the pudendal nerve control the sphincter of urinary bladder. Urinary intention is mediated by the pelvic and the hypogastric nerves. These peripheral nerves are controlled by the urination center of the brain stem. The function of the urination center at the brain stem is under the control of the frontal lobe of the brain. In short, the function of the external urethral sphincter (voluntary muscle) that is under the control of the frontal lobe of the brain relates strongly to UI. These neural bases of excretion mechanisms generate a hypothesis that the frontal lobe function in the UI group must
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be inferior to that of the control group, because UI is caused by any acquired dysfunction of the frontal cortex in middle- and upper middle-aged people. Therefore, cognitive test performance of frontal lobe in UI must be inferior to that of the control group, whereas cognitive performances that related to the other area (e.g., temporal area) do not show a group difference. Our findings seem to correspond with our hypothesis, namely that prefrontal cortex related index, such as LFT and D-CAT (hit 3), showed a significant group difference between the UI and the control group; that is, the performance of UI was significantly inferior to that of the control. Using a new brain imaging technique, NIRS, Hatta et al. (2008, 2009) confirmed robust prefrontal cortex activation in LFT and D-CAT (hit 3) indices. On the other hand, temporal area related indices such as LMT and MRT showed no difference between UI and control groups. Stroop test performance showed rather complicated results, although not inconsistent with our hypothesis. In short, our present findings indicate an important role of prefrontal cortex on the incidence of UI in the middle and upper middle non-disabled elderly. This indication recalls the study by Inzitari et al. (2008) where they examined whether subtle, but clinically detectable, neurological abnormalities (SNAs) are associated with lower cognitive and physical performance in elderly persons (the mean age was 71.9 years). They found that SNAs have a prospective association with cognitive and physical performance decline in older community-dwelling persons. Compared with low SNA score people, higher SNA score people have an increased risk of cognitive dysfunction and death. These studies, along with the present findings, generate an intuitive flow-chart of a negative spiral, that subtle neurological abnormality (e.g., UI) reflects a decline of cognitive performance and self-esteem, which brings about hesitation in anti-human communication situations, followed by a tendency to stay at home, thus bringing about a further decline of cognitive function in elderly people and precipitating causes of UI. If we combine the idea of SNAs by Inzitari et al. (2008) with our findings, we may be able to regard the UI incidence as a sign for SNA. As our findings, as already may be seen, show a strong relation between UI and cognitive tasks decline (LFT and D-CAT (hit 3)) that reflects prefrontal cortex function, we may be able to consider ways to curb the incidence of UI, or to correct precipitating processes by introducing some cognitive training to activate prefrontal cortex. If we develop a program to sustain cognitive function corresponding with prefrontal area from early middle age of intact people, the incidence of UI could be retarded. The retardation of UI incidence would give rise to positive self-esteem among middle-aged people, and expand inter-human communication, and thus create a positive spiral. This positive spiral must surely be a preventive activity to lessen UI prevalence. If we further expand these ideas, this may begin to play some role in relieving the psychosocial and economical burden of UI in elderly populations (Herzog et al., 1989; Ekelund et al., 1993; DuBeau et al., 1998; Wagner and Hu, 1998). Conflict of interest statement None. Acknowledgements This study was the part of Yakumo study and has been supported by the Grant-in-Aid for sicentific research (B) to the first author (#19330158). Authors expressed great appreciation to the support of staff members engaged with Yakumo Study of Yakumo Town and all participants.
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