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Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention., CC BY 4.0© 2022 The AuthorsCorresponding author at: Department of Health, Blekinge Institute of Technology, Valhallavägen 1, 371 41 Karlskrona, Sweden. E-mail address: anders.behrens@bth.se (A. Behrens). SNAC is financially supported by the Ministry of Health and Social Affairs, Sweden, and the participating county councils, municipalities, and university departments.

Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention., CC BY 4.0© 2022 The AuthorsCorresponding author at: Department of Health, Blekinge Institute of Technology, Valhallavägen 1, 371 41 Karlskrona, Sweden. E-mail address: anders.behrens@bth.se (A. Behrens). SNAC is financially supported by the Ministry of Health and Social Affairs, Sweden, and the participating county councils, municipalities, and university departments.

Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention., CC BY 4.0© 2022 The AuthorsCorresponding author at: Department of Health, Blekinge Institute of Technology, Valhallavägen 1, 371 41 Karlskrona, Sweden. E-mail address: anders.behrens@bth.se (A. Behrens). SNAC is financially supported by the Ministry of Health and Social Affairs, Sweden, and the participating county councils, municipalities, and university departments.

Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention., CC BY 4.0© 2022 The AuthorsCorresponding author at: Department of Health, Blekinge Institute of Technology, Valhallavägen 1, 371 41 Karlskrona, Sweden. E-mail address: anders.behrens@bth.se (A. Behrens). SNAC is financially supported by the Ministry of Health and Social Affairs, Sweden, and the participating county councils, municipalities, and university departments.

Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention., CC BY 4.0© 2022 The AuthorsCorresponding author at: Department of Health, Blekinge Institute of Technology, Valhallavägen 1, 371 41 Karlskrona, Sweden. E-mail address: anders.behrens@bth.se (A. Behrens). SNAC is financially supported by the Ministry of Health and Social Affairs, Sweden, and the participating county councils, municipalities, and university departments.

Objective: The Clock Drawing Test (CDT) is frequently used to screen for cognitive impairment, however, normative data for Rouleau et al.’s (1992) scoring system are scarce. The present study aims to provide norms for Rouleau et al.’s (1992) scoring system that are tailored to Quebec French-speaking mid and older-aged healthy adults. Methods: Six researchers from various research centers across the Province of Quebec (Canada) sent anonymous data for 593 (391 women) healthy community-dwelling volunteers (age range: 43-93 years; education range: 5-23 years) who completed the CDT “drawing on command” version. This command version (setting the clock hands to 11:10, without a pre-drawn circle) was administrated as part of a more extensive neuropsychological assessment, or along with cognitive screening instruments. Each drawn clock was scored according to the quantitative criteria set by Rouleau et al.’s (1992) scoring system. Results: CDT scores were significantly correlated with age (r(592) = -.132, p = .001) and years of education (r(592) = .116, p = .005), but not with sex (r(592) = .065, p = .112). Since data were skewed towards higher test scores, the percentiles method was used for analysis. Percentile ranks stratified by age and education are presented. Conclusion: These normative data for Rouleau et al.’s (1992) scoring system will contribute towards adequately screening for cognitive decline in Quebec French-speaking healthy adults, by also taking into account individual characteristics such as age and education.

Background: Differentiating mild cognitive impairment (MCI) from subjective cognitive decline (SCD) is important because of the higher progression rate to dementia for MCI and when considering future disease-modifying drugs that will have treatment indications at the MCI stage. Objective: We examined if the two most widely-used cognitive tests, the Mini-Mental State Examination (MMSE) and clock-drawing test (CDT), and a test of attention/executive function (AQT) accurately can differentiate MCI from SCD. Methods: We included 466 consecutively recruited non-demented patients with cognitive complaints from the BioFINDER study who had been referred to memory clinics, predominantly from primary care. They were classified as MCI (n = 258) or SCD (n = 208) after thorough neuropsychological assessments. The accuracy of MMSE, CDT, and AQT for identifying MCI was examined both in training and validation samples and in the whole population. Results: As a single test, MMSE had the highest accuracy (sensitivity 73%, specificity 60%). The best combination of two tests was MMSE < 27 points or AQT > 91 seconds (sensitivity 56%, specificity 78%), but in logistic regression models, their AUC (0.76) was not significantly better than MMSE alone (AUC 0.75). CDT and AQT performed significantly worse (AUC 0.71; p < 0.001-0.05); otherwise no differences were seen between any combination of two or three tests. Conclusion: Neither single nor combinations of tests could differentiate MCI from SCD with adequately high accuracy. There is a great need to further develop, validate, and implement accurate screening-tests for primary care to improve accurate identification of MCI among individuals that seek medical care due to cognitive symptoms.

Objective: The Clock Drawing Test (CDT) is frequently used to screen for cognitive impairment, however, normative data for Rouleau et al.’s (1992) scoring system are scarce. The present study aims to provide norms for Rouleau et al.’s (1992) scoring system that are tailored to Quebec French-speaking mid and older-aged healthy adults. Methods: Six researchers from various research centers across the Province of Quebec (Canada) sent anonymous data for 593 (391 women) healthy community-dwelling volunteers (age range: 43-93 years; education range: 5-23 years) who completed the CDT “drawing on command” version. This command version (setting the clock hands to 11:10, without a pre-drawn circle) was administrated as part of a more extensive neuropsychological assessment, or along with cognitive screening instruments. Each drawn clock was scored according to the quantitative criteria set by Rouleau et al.’s (1992) scoring system. Results: CDT scores were significantly correlated with age (r(592) = -.132, p = .001) and years of education (r(592) = .116, p = .005), but not with sex (r(592) = .065, p = .112). Since data were skewed towards higher test scores, the percentiles method was used for analysis. Percentile ranks stratified by age and education are presented. Conclusion: These normative data for Rouleau et al.’s (1992) scoring system will contribute towards adequately screening for cognitive decline in Quebec French-speaking healthy adults, by also taking into account individual characteristics such as age and education.

Objective: To explore the utility of cognitive tests, that did not rely on spoken language from participants for decision making about eligibility for treatment with Anti-cholinesterase Inhibitors (AchI). Methods: A cross-sectional design was used. Data was collected from 20 participants, aged 65 to 90 years (M, 77.6: SD, 7.2), with dementia, or cognitive difficulties. The sample comprised of eleven males and nine females. The Mini-Mental State Examination (MMSE), and six alternative cognitive tests were administered, these were; the Rey Complex Figure Test (RCFT), Ravens Colour Progressive Matrices (RCPM), Symbol Digit Modalities Test (SDMT), Brixton Test, Clock Drawing Test (CDT), and Colour Trails Test (CTT). Results: There was statistically significant correlations between the MMSE and the following cognitive tests: RCFT visual construction subtest(r= .609; P<.006), the RCFT recognition subtest (r= .496; P<.031), RCPM (r= .452; p<.045), the SDMT (r=.670; P<.001), the CTT 1 (Rho=-.576; P<.012) and the CDT (r=-.577; P<.008). The area under the ROC curve values were as follows: RCFT visual construction (0.750, 95%, CI .524 - .976), RCFT recognition memory (0.801, 95%, CI .590 – 1.012), RCPM (0.573, 95%, CI 0.298 – 0.848), SDMT (0.708, 95%, CI 0.469 – 0.947), CTT1 (0.818, 95%, CI 0.610 – 1.027) and the CDT (0.734, 95%, CI 0.479 – 0.990). Cut-off scores with adequate sensitivity and specificity were identified for all the above measures apart from the RCPM, which had predictive accuracy that was equal to chance. Conclusions: Cognitive tests which do not require spoken language have utility in differentiating between those who are and are not eligible for treatment with AchI, as defined by the cut-off (<20) on the MMSE in the National Institute for Clinical Excellence guidelines (NICE, 2007).

Objective: To explore the utility of cognitive tests, that did not rely on spoken language from participants for decision making about eligibility for treatment with Anti-cholinesterase Inhibitors (AchI). Methods: A cross-sectional design was used. Data was collected from 20 participants, aged 65 to 90 years (M, 77.6: SD, 7.2), with dementia, or cognitive difficulties. The sample comprised of eleven males and nine females. The Mini-Mental State Examination (MMSE), and six alternative cognitive tests were administered, these were; the Rey Complex Figure Test (RCFT), Ravens Colour Progressive Matrices (RCPM), Symbol Digit Modalities Test (SDMT), Brixton Test, Clock Drawing Test (CDT), and Colour Trails Test (CTT). Results: There was statistically significant correlations between the MMSE and the following cognitive tests: RCFT visual construction subtest(r= .609; P<.006), the RCFT recognition subtest (r= .496; P<.031), RCPM (r= .452; p<.045), the SDMT (r=.670; P<.001), the CTT 1 (Rho=-.576; P<.012) and the CDT (r=-.577; P<.008). The area under the ROC curve values were as follows: RCFT visual construction (0.750, 95%, CI .524 - .976), RCFT recognition memory (0.801, 95%, CI .590 – 1.012), RCPM (0.573, 95%, CI 0.298 – 0.848), SDMT (0.708, 95%, CI 0.469 – 0.947), CTT1 (0.818, 95%, CI 0.610 – 1.027) and the CDT (0.734, 95%, CI 0.479 – 0.990). Cut-off scores with adequate sensitivity and specificity were identified for all the above measures apart from the RCPM, which had predictive accuracy that was equal to chance. Conclusions: Cognitive tests which do not require spoken language have utility in differentiating between those who are and are not eligible for treatment with AchI, as defined by the cut-off (<20) on the MMSE in the National Institute for Clinical Excellence guidelines (NICE, 2007).