AFFECTIVE PROBLEMS AND COGNITIVE DECLINE: A SYSTEMATIC REVIEW AND META-ANALYSIS

Poster Presentations: Tuesday, July 18, 2017

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THE ASSOCIATION BETWEEN NEIGHBORHOOD SOCIO-ECONOMIC STATUS, SLEEP QUALITY, AND COGNITIVE DECLINE IN THE HEALTH AND RETIREMENT STUDY

Kathleen M. Hayden1, Elizabeth Handing1, Ramon Casanova1, Maragatha Kuchibhatla2, Santiago Saldana1, Michael W. Lutz3, Brenda L. Plassman3, 1Wake Forest School of Medicine, Winston-Salem, NC, USA; 2Duke University Medical Center, Durham, NC, USA; 3Duke University Bryan ADRC, Durham, NC, USA. Contact e-mail: khayden@ wakehealth.edu Background: Recent studies have reported associations between the

residential environment and cognitive decline. These environmental characteristics may similarly have an effect on sleep quality, which is also associated with cognitive decline. We sought to evaluate the combined effects of neighborhood socio-economic status (NSES) and sleep quality on cognitive decline in a nationally representative cohort of older adults from the Health and Retirement Study (HRS). Methods: Participants from the HRS aged 65+ with DNA samples and multiple cognitive observations were included in the study. Cognition was evaluated biennially with the abbreviated Telephone Interview for Cognitive Status (TICS-m). A NSES index was developed based on 6 factors (unemployment, poverty, public assistance, education levels, income, and household characteristics). A sleep quality scale was developed based on self-reported trouble falling asleep, waking during the night, waking too early, and feeling rested. Covariates included age, sex, education, race, APOEε4 status, and self-reported hypertension, diabetes, history of any heart condition, and stroke, modeled as age-varying covariates. Random effects modeling was used to evaluate cognitive change over time in four groups of participants based on quartiles of NSES and sleep quality. Potential interactions between NSES and sleep were tested using these as continuous variables. Results: NSES and sleep were each significantly associated with cognitive decline, and there was a modest but significant interaction (p¼0.02) between the two. Models with participants in four groups of high/low sleep quality and high/low NSES revealed significant differences between high and low NSES (p<.001), and between high/low sleep quality among those with low NSES. Low sleep quality was more strongly associated with cognitive decline among participants with low NSES than those with high NSES, which had no significant difference. Differences between the four groups were driven primarily by differences in high vs low NSES. Conclusions: Both sleep and NSES were associated with cognitive decline in the HRS, but the association between sleep and cognition appeared stronger among those with low NSES. The association between low NSES, poor sleep quality, and cognitive decline was roughly equivalent to the association between APOE ε4 and cognitive decline. P3-521

AGE AS A DEMOGRAPHIC VARIABLE RELATED WITH LACK OF METACOGNITION IN MIDDLE-AGED AND OLDER ADULTS WITH HIGH EDUCATIONAL LEVEL

Alvaro Teixeira da Costa, Renata Brant de Souza Melo, Antonio Pereira Gomes Neto, Ronnielly Melo Tavares, Santa Casa de Belo Horizonte – MG – Brazil, Belo Horizonte, Brazil. Contact e-mail: [email protected] Background: Advancing toward earlier detection and diagnosis of Alz-

heimer Disease (AD) may help to reach an effective therapy for it. It has already been shown that metacognition (insight about one’s own correct and incorrect judgments) is a consistently significant predictor of

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everyday functioning. The relationship between altered metacognition and dementia is still not fully well understood, but its correlations with functionality and its misjudge characteristic raises suspicion that it may be seen in an early stage of a neurodegenerative disease. People with lack of metacognition (LM) did not look for medical assistance until got dysfunctional, losing a precious time for interventions. Despite its importance, little is known about the prevalence of LM and how demographic variables impact on them. The objective of this study is to verify relationship between demographic variables and LM in presumed normal middle-aged and older adults with higher educational levels. Methods: This is a cross-sectional study, population-based, with non-probabilistic convenience sample. We selected patients over 40 years and with 12 or more years of education in a public square of Belo Horizonte’s city (third metropolitan area from Brazil). The sample (n ¼ 66) was subjected to a metacognitive questionnaire (MAC-Q test) and a brief cognitive battery (MoCA test and semantic verbal fluency test). They were divided into four groups according to the results: Normal Group (NG), Subjective Memory Complaints (SMC), Lack of Metacognition (LM) and Objective Cognitive Impairment (OCI). These four groups were compared for age, gender, marital status, educational level, laboral status, city of born (capital/country town), and calculated the mean and standard deviation, median, minimum and maximum for each. Results: Differences about median of age was found, with statistical significance, between groups NG and LM (57,5y vs. 67y; p¼0,044), NG and OCI (57,5y vs. 76,5y; p<0,001), SMC and OCI (59y vs. 76,5y; p<0,001) and LM and OCI (67y vs. 76,5y; p¼0,016). Conclusions: This study suggests that age can help to distinguish who has lack of metacognition among population with higher educational levels. Therefore, this can be the basis for the elaboration of a cognitive screening for this profile. P3-522

AFFECTIVE PROBLEMS AND COGNITIVE DECLINE: A SYSTEMATIC REVIEW AND META-ANALYSIS

Amber John1, Urvisha Patel1, Jennifer M. Rusted1, Marcus Richards2, Darya Gaysina1, 1University of Sussex, Falmer, United Kingdom; 2MRC Unit for Lifelong Health and Ageing at UCL, London, United Kingdom. Contact e-mail: aj316@sussex. ac.uk Background: Previous evidence suggests that the presence of affective problems, such as depression and/or anxiety, may confer a heightened risk for late-life dementia. However, due to conflicting findings and a lack of attempts to synthesise existing data, the extent to which affective symptoms may influence cognitive decline, even many years prior to the clinical threshold for a diagnosis of dementia, is not clear. The present study systematically reviews and synthesises the current evidence surrounding the association between affective problems and cognitive decline across the life course. Methods: An electronic search of PubMed, PsycInfo and ScienceDirect was conducted to identify studies on the association between depression and/or anxiety and subsequent cognitive decline. Key inclusion criteria were prospective, longitudinal studies with a minimum follow-up period of one year. Crosssectional, experimental, and clinical (case-control) studies were excluded. Reference lists of relevant papers were scanned for any additional articles of interest. Data extraction and methodological quality assessment using the STROBE checklist were conducted independently by two raters. As a next step, mixed-effects metaanalyses will be conducted, with consideration of a number of potential moderators, including mean age of sample at baseline, length of follow-up, and type of affective disorder. Results: After

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Poster Presentations: Tuesday, July 18, 2017

removal of duplicate references, all papers were screened for eligibility using a three-step process: 1) title screening (N¼20,954); 2) abstract screening (N¼981); and 3) full text screening (N¼172). Inter-rater reliability at each stage of screening was >96%. A total of 87 studies, with an overall sample size of 256,592 participants, met eligibility criteria, with 69 studies measuring depression only (n¼172,511), 6 -anxiety only (n¼28,541), 6 –both (n¼6,251), and 6 -other affective problems (n¼49,289). The results of the meta-analyses will be presented and discussed with a focus on the effects of the key moderators that can influence the link between affective symptoms and cognitive decline. Conclusions: Results of the present study will improve current understanding of the temporal nature of the association between affective problems and cognition across the life-course. This will have important implications for the identification of individuals who are at a particularly high risk for accelerated cognitive decline and dementia. P3-523

IDENTIFICATION OF LATENT RESERVE RISK FACTORS FOR DEMENTIA IN TWO LARGE PROSPECTIVE STUDIES: CONFIRMATORY FACTOR ANALYSIS

Amy R. Borenstein1, James A. Mortimer1, Alfred Mbah1, Paul K. Crane2, Eric B. Larson3, 1University of South Florida, Tampa, FL, USA; 2University of Washington, Seattle, WA, USA; 3Group Health Research Institute/Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA. Contact e-mail: [email protected] Background: The measurement of reserve in longitudinal studies is

important given its potential role in delaying dementia onset. We used exploratory factor analysis followed by structural equation modeling to identify latent factors related to Alzheimer and vascular neuropathology as well as reserve. Methods: Baseline assessments of reaction time, global cognition, education, subjective cognitive impairment, olfactory impairment, hypertension, diabetes, stroke, and APOE-e4 were subjected to exploratory factor analysis in the Kame Project and the Adult Changes in Thought (ACT) Study. Confirmatory factor analysis was used to create latent variables that were then used in Cox proportional hazard models to predict

incident dementia. Results: In exploratory analyses, 3 factors with eigenvalues >1 were identified in the Kame Project. One included subjective cognitive impairment, olfactory impairment and the presence of APOE-e4 (“Alzheimer”); another included hypertension, diabetes and stroke (“Vascular”); and a third included simple reaction time and education (“Reserve”). The same 3 factors were identified in the ACT study, with the exception that reaction time was replaced by the initial CASI score. In this study, APOE4 did not load on the “Alzheimer” factor and instead appeared as its own 4th factor. Confirmatory factor analysis demonstrated significant loadings on the same indicators. The latent variables created were used to predict incident dementia. In the Kame model (n¼1360, 104 cases, mean follow-up¼6.6 years), significant hazard ratios were seen for the “Alzheimer” factor [2.17 (1.48-3.17)] and the “Reserve” factor [0.72 (0.59-0.87)], but not the “Vascular” factor [1.17 (0.86-1.58)]. In the ACT Study (n¼2329, 761 cases, mean follow-up¼7.8 years), significant hazard ratios were seen for “Alzheimer” [1.10 (1.02-1.19)], “Reserve” [0.81 (0.76-0.86)], and APOE4 [1.68 (1.43-1.97)], but not for “Vascular” [1.05 (0.971.13)]. Because the data for ACT were based on deceased participants only, the Kame analysis was repeated using only those who died during the study, resulting in similar findings (e.g.,“Reserve” HR ¼ 0.72). Analyses in which baseline CASI was substituted for reaction time in Kame as an indicator of reserve produced very similar findings. Conclusions: Reserve measured by educational attainment and performance on tests associated with IQ accounted for a substantial reduction in risk of incident dementia in both studies. P3-524

EXPLORING LATE-LIFE RISK FACTORS OF ALZHEIMER’S DISEASE AND OTHER AGE-RELATED DEMENTIAS IN CPRD

Bowen Su1, Anita Kulatilake1, Roger Newson1, Ioanna Tzoulaki1, Michael Soljak1, Lefkos T. Middleton2, 1Imperial College London, London, United Kingdom; 2Imperial College, London, United Kingdom. Contact e-mail: [email protected] Background: There is accumulating evidence suggesting that Alz-

heimer’s disease (AD) and other late-life dementias share a number of modifiable risk factors with cardiovascular diseases (CVD). The objective of our study is to evaluate such risk factors in a truly population- based, large-scale study design, using the UK Clinical Practice Research Datalink (CPRD), the Hospital Episode Statistics (HES) and the Office for National Statistics (ONS) mortality data. Methods: All the eligible patients aged over the age of 50 years were selected from CPRD. Patients with dementia were identified, using a dementia case identification algorithm using diagnosis by general practitioner (in CPRD), a secondary care specialist (HES), and use of drugs having dementia as primary indication. Risk factor data was extracted from CPRD with a 10 years follow-up, prior to dementia diagnosis. Logistic regression model was used to estimate the probability of developing dementia based on statistically significant risk or protective factors from likelihood ratio test. Inverse probability weight was used to replace missing values. Results: A total of 212,085 patients had a GP diagnosis of dementia, an additional 100,961 patients had a dementia diagnosis in HES, whilst 8,650 patients had an indicative score from cognitive impairment tests and 4,659 patients were on specific dementia drugs without being part of the previous categories. Overall, 326,355 patients with dementia were identified. Presence of diabetes, coronary heart disease (CHD), depression, cerebrovascular disease, hypertension, high body mass index (BMI), increased alcohol chronic consumption, smoking, lower education, higher age and male gender were all strongly associated with the incidence of dementia with ORs